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36 | data | https://github.com/joke2k/faker | [] | null | [] | [] | null | null | null | joke2k/faker | faker | 16,741 | 1,851 | 220 | Python | https://faker.readthedocs.io | Faker is a Python package that generates fake data for you. | joke2k | 2024-01-14 | 2012-11-12 | 585 | 28.610107 | null | Faker is a Python package that generates fake data for you. | ['dataset', 'fake', 'fake-data', 'faker', 'faker-generator', 'test-data', 'test-data-generator', 'testing'] | ['dataset', 'fake', 'fake-data', 'faker', 'faker-generator', 'test-data', 'test-data-generator', 'testing'] | 2024-01-10 | [('snyk/faker-security', 0.7436192631721497, 'security', 0), ('lk-geimfari/mimesis', 0.6268561482429504, 'data', 3)] | 555 | 7 | null | 5.96 | 67 | 48 | 136 | 0 | 70 | 30 | 70 | 67 | 109 | 90 | 1.6 | 65 |
125 | ml | https://github.com/onnx/onnx | [] | null | [] | [] | null | null | null | onnx/onnx | onnx | 16,209 | 3,620 | 438 | Python | https://onnx.ai/ | Open standard for machine learning interoperability | onnx | 2024-01-14 | 2017-09-07 | 333 | 48.57149 | https://avatars.githubusercontent.com/u/31675368?v=4 | Open standard for machine learning interoperability | ['deep-learning', 'deep-neural-networks', 'dnn', 'keras', 'machine-learning', 'ml', 'mxnet', 'neural-network', 'onnx', 'pytorch', 'scikit-learn', 'tensorflow'] | ['deep-learning', 'deep-neural-networks', 'dnn', 'keras', 'machine-learning', 'ml', 'mxnet', 'neural-network', 'onnx', 'pytorch', 'scikit-learn', 'tensorflow'] | 2024-01-12 | [('microsoft/onnxruntime', 0.727009654045105, 'ml', 6), ('tensorflow/tensorflow', 0.7098345756530762, 'ml-dl', 6), ('polyaxon/polyaxon', 0.6912744641304016, 'ml-ops', 7), ('explosion/thinc', 0.6653851866722107, 'ml-dl', 5), ('mlflow/mlflow', 0.6629000902175903, 'ml-ops', 2), 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| 305 | 2 | null | 9.48 | 272 | 168 | 77 | 0 | 4 | 4 | 4 | 272 | 391 | 90 | 1.4 | 65 |
153 | nlp | https://github.com/flairnlp/flair | [] | null | [] | [] | null | null | null | flairnlp/flair | flair | 13,342 | 2,054 | 204 | Python | https://flairnlp.github.io/flair/ | A very simple framework for state-of-the-art Natural Language Processing (NLP) | flairnlp | 2024-01-13 | 2018-06-11 | 294 | 45.358912 | https://avatars.githubusercontent.com/u/59021421?v=4 | A very simple framework for state-of-the-art Natural Language Processing (NLP) | ['machine-learning', 'named-entity-recognition', 'natural-language-processing', 'nlp', 'pytorch', 'semantic-role-labeling', 'sequence-labeling', 'word-embeddings'] | ['machine-learning', 'named-entity-recognition', 'natural-language-processing', 'nlp', 'pytorch', 'semantic-role-labeling', 'sequence-labeling', 'word-embeddings'] | 2023-12-18 | [('franck-dernoncourt/neuroner', 0.7272414565086365, 'nlp', 3), ('allenai/allennlp', 0.6880818605422974, 'nlp', 3), ('nltk/nltk', 0.6725092530250549, 'nlp', 3), ('explosion/spacy', 0.6546562910079956, 'nlp', 4), ('explosion/spacy-models', 0.6428545117378235, 'nlp', 3), ('sloria/textblob', 0.6279769539833069, 'nlp', 2), ('keras-team/keras-nlp', 0.6184731125831604, 'nlp', 3), ('norskregnesentral/skweak', 0.602255642414093, 'nlp', 1), ('explosion/spacy-llm', 0.6013752222061157, 'llm', 4), ('rasahq/rasa', 0.5888329744338989, 'llm', 3), ('alibaba/easynlp', 0.5845892429351807, 'nlp', 3), ('deepset-ai/farm', 0.5659800171852112, 'nlp', 2), ('graykode/nlp-tutorial', 0.561720073223114, 'study', 3), ('huggingface/transformers', 0.5504770874977112, 'nlp', 4), ('pemistahl/lingua-py', 0.5448145270347595, 'nlp', 2), ('llmware-ai/llmware', 0.5408936738967896, 'llm', 3), ('koaning/whatlies', 0.5374947190284729, 'nlp', 1), ('paddlepaddle/paddlenlp', 0.5343381762504578, 'llm', 1), ('plasticityai/magnitude', 0.5328223705291748, 'nlp', 4), ('jonasgeiping/cramming', 0.5266839265823364, 'nlp', 1), ('koaning/embetter', 0.5184030532836914, 'data', 0), ('ibm/transition-amr-parser', 0.5182547569274902, 'nlp', 2), ('maartengr/bertopic', 0.5175113677978516, 'nlp', 2), ('jalammar/ecco', 0.517105758190155, 'ml-interpretability', 3), ('explosion/spacy-streamlit', 0.5156773328781128, 'nlp', 4), ('bigscience-workshop/promptsource', 0.5140012502670288, 'nlp', 3), ('infinitylogesh/mutate', 0.5080118775367737, 'nlp', 0), ('qanastek/drbert', 0.5062006711959839, 'llm', 2), ('sebischair/lbl2vec', 0.5040925145149231, 'nlp', 4), ('argilla-io/argilla', 0.5028916597366333, 'nlp', 3)] | 251 | 5 | null | 11.87 | 85 | 62 | 68 | 1 | 5 | 5 | 5 | 85 | 119 | 90 | 1.4 | 65 |
143 | nlp | https://github.com/ukplab/sentence-transformers | ['sentence-embeddings', 'semantic-search', 'information-retrieval'] | null | [] | [] | null | null | null | ukplab/sentence-transformers | sentence-transformers | 12,848 | 2,226 | 130 | Python | https://www.SBERT.net | Multilingual Sentence & Image Embeddings with BERT | ukplab | 2024-01-14 | 2019-07-24 | 235 | 54.473652 | https://avatars.githubusercontent.com/u/9532046?v=4 | Multilingual Sentence & Image Embeddings with BERT | [] | ['information-retrieval', 'semantic-search', 'sentence-embeddings'] | 2024-01-10 | [('jina-ai/clip-as-service', 0.7321420311927795, 'nlp', 0), ('jina-ai/finetuner', 0.5992518663406372, 'ml', 0), ('amansrivastava17/embedding-as-service', 0.5738234519958496, 'nlp', 0), ('ddangelov/top2vec', 0.5732832551002502, 'nlp', 1), ('alibaba/easynlp', 0.551360011100769, 'nlp', 0), ('muennighoff/sgpt', 0.5446346402168274, 'llm', 3), ('neuml/txtai', 0.5237442255020142, 'nlp', 3), ('ai21labs/in-context-ralm', 0.5168312788009644, 'llm', 0), ('qdrant/fastembed', 0.5122830867767334, 'ml', 0), ('extreme-bert/extreme-bert', 0.50993812084198, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5090245604515076, 'llm', 0), ('koaning/whatlies', 0.5054284334182739, 'nlp', 0), ('intellabs/fastrag', 0.5005632042884827, 'nlp', 2)] | 131 | 4 | null | 1.44 | 196 | 125 | 54 | 0 | 0 | 7 | 7 | 196 | 300 | 90 | 1.5 | 65 |
798 | web | https://github.com/encode/httpx | [] | null | [] | [] | null | null | null | encode/httpx | httpx | 11,723 | 816 | 113 | Python | https://www.python-httpx.org/ | A next generation HTTP client for Python. 🦋 | encode | 2024-01-14 | 2019-04-04 | 251 | 46.572645 | https://avatars.githubusercontent.com/u/19159390?v=4 | A next generation HTTP client for Python. 🦋 | ['asyncio', 'http', 'trio'] | ['asyncio', 'http', 'trio'] | 2024-01-12 | [('encode/uvicorn', 0.8501601815223694, 'web', 2), ('aio-libs/aiohttp', 0.8457793593406677, 'web', 2), ('pallets/quart', 0.748035192489624, 'web', 1), ('neoteroi/blacksheep', 0.7281930446624756, 'web', 2), ('psf/requests', 0.7030969858169556, 'web', 1), ('alirn76/panther', 0.6786492466926575, 'web', 0), ('requests/toolbelt', 0.6686779856681824, 'util', 1), ('cherrypy/cherrypy', 0.65858393907547, 'web', 1), ('simple-salesforce/simple-salesforce', 0.6496359705924988, 'data', 0), ('timofurrer/awesome-asyncio', 0.640356183052063, 'study', 1), ('klen/muffin', 0.6186836957931519, 'web', 2), ('falconry/falcon', 0.6106772422790527, 'web', 1), ('websocket-client/websocket-client', 0.6006039381027222, 'web', 0), ('encode/starlette', 0.5981119275093079, 'web', 1), ('miguelgrinberg/python-socketio', 0.5959307551383972, 'util', 1), ('masoniteframework/masonite', 0.5954501628875732, 'web', 0), ('python-trio/trio', 0.5947321057319641, 'perf', 1), ('pylons/waitress', 0.594509482383728, 'web', 0), ('hugapi/hug', 0.5931265950202942, 'util', 1), ('replicate/replicate-python', 0.5832346677780151, 'ml', 0), ('samuelcolvin/aioaws', 0.5720120072364807, 'data', 1), ('pallets/werkzeug', 0.5651618838310242, 'web', 1), ('agronholm/anyio', 0.558357298374176, 'perf', 2), ('airtai/faststream', 0.5473020672798157, 'perf', 1), ('webpy/webpy', 0.5403591394424438, 'web', 0), ('benoitc/gunicorn', 0.5388432145118713, 'web', 1), ('locustio/locust', 0.5382368564605713, 'testing', 1), ('aio-libs/aiobotocore', 0.536460280418396, 'util', 1), ('snyk-labs/pysnyk', 0.5362645983695984, 'security', 0), ('radiantearth/radiant-mlhub', 0.5330476760864258, 'gis', 0), ('bottlepy/bottle', 0.5296392440795898, 'web', 0), ('huge-success/sanic', 0.5279699563980103, 'web', 1), ('magicstack/uvloop', 0.5275475978851318, 'util', 1), ('samuelcolvin/arq', 0.525906503200531, 'data', 1), ('paramiko/paramiko', 0.5251051187515259, 'util', 0), ('pallets/flask', 0.5245396494865417, 'web', 0), ('pylons/pyramid', 0.5153858661651611, 'web', 0), ('tornadoweb/tornado', 0.5143762230873108, 'web', 0), ('reflex-dev/reflex', 0.5139403939247131, 'web', 0), ('pytest-dev/pytest-asyncio', 0.5099304914474487, 'testing', 1), ('starlite-api/starlite', 0.5098319053649902, 'web', 1), ('amzn/ion-python', 0.5086729526519775, 'data', 0), ('geeogi/async-python-lambda-template', 0.5077229142189026, 'template', 0), ('nasdaq/data-link-python', 0.5050049424171448, 'finance', 0), ('getsentry/responses', 0.5034039616584778, 'testing', 0), ('ethereum/web3.py', 0.5025968551635742, 'crypto', 0), ('hydrosquall/tiingo-python', 0.5019758939743042, 'finance', 0), ('pyston/pyston', 0.5002996325492859, 'util', 0)] | 212 | 5 | null | 2.94 | 113 | 90 | 58 | 0 | 6 | 17 | 6 | 113 | 208 | 90 | 1.8 | 65 |
11 | perf | https://github.com/dask/dask | [] | null | [] | [] | null | null | null | dask/dask | dask | 11,689 | 1,665 | 213 | Python | https://dask.org | Parallel computing with task scheduling | dask | 2024-01-14 | 2015-01-04 | 473 | 24.697555 | https://avatars.githubusercontent.com/u/17131925?v=4 | Parallel computing with task scheduling | ['dask', 'numpy', 'pandas', 'pydata', 'scikit-learn', 'scipy'] | ['dask', 'numpy', 'pandas', 'pydata', 'scikit-learn', 'scipy'] | 2024-01-12 | [('nalepae/pandarallel', 0.7318655252456665, 'pandas', 1), ('dask/distributed', 0.719694972038269, 'perf', 2), ('agronholm/apscheduler', 0.6700900197029114, 'util', 0), ('ipython/ipyparallel', 0.64837247133255, 'perf', 0), ('joblib/joblib', 0.6337271332740784, 'util', 0), ('scipy/scipy', 0.6020888686180115, 'math', 1), ('jmcarpenter2/swifter', 0.60169517993927, 'pandas', 2), ('numpy/numpy', 0.5977861285209656, 'math', 1), ('geopandas/dask-geopandas', 0.5673131942749023, 'gis', 0), ('backtick-se/cowait', 0.5500026941299438, 'util', 1), ('samuelcolvin/arq', 0.5444415211677551, 'data', 0), ('dbader/schedule', 0.5425211191177368, 'util', 0), ('hyperopt/hyperopt', 0.5399159789085388, 'ml', 0), ('blaze/blaze', 0.5343106985092163, 'pandas', 0), ('joblib/loky', 0.5317108035087585, 'perf', 0), ('eventual-inc/daft', 0.5266561508178711, 'pandas', 0), ('dask/dask-ml', 0.526610255241394, 'ml', 0), ('eventlet/eventlet', 0.5214966535568237, 'perf', 0), ('bogdanp/dramatiq', 0.5178118944168091, 'util', 0), ('fugue-project/fugue', 0.5079086422920227, 'pandas', 2), ('python-trio/trio', 0.5067204236984253, 'perf', 0), ('parallel-domain/pd-sdk', 0.5014457702636719, 'data', 0)] | 592 | 6 | null | 9.31 | 292 | 175 | 110 | 0 | 0 | 31 | 31 | 292 | 454 | 90 | 1.6 | 65 |
38 | jupyter | https://github.com/jupyter/notebook | [] | null | [] | [] | null | null | null | jupyter/notebook | notebook | 10,849 | 4,462 | 321 | Jupyter Notebook | https://jupyter-notebook.readthedocs.io/ | Jupyter Interactive Notebook | jupyter | 2024-01-13 | 2015-04-09 | 459 | 23.599441 | https://avatars.githubusercontent.com/u/7388996?v=4 | Jupyter Interactive Notebook | ['jupyter', 'jupyter-notebook', 'notebook'] | ['jupyter', 'jupyter-notebook', 'notebook'] | 2024-01-02 | [('jupyter-widgets/ipywidgets', 0.8538753390312195, 'jupyter', 0), ('jupyter/nbformat', 0.7493022680282593, 'jupyter', 0), ('jupyterlab/jupyterlab-desktop', 0.7161470651626587, 'jupyter', 2), ('jupyter/nbconvert', 0.7077092528343201, 'jupyter', 0), ('voila-dashboards/voila', 0.6948908567428589, 'jupyter', 2), ('ipython/ipykernel', 0.6881211400032043, 'util', 2), ('mwouts/jupytext', 0.6791135668754578, 'jupyter', 1), ('computationalmodelling/nbval', 0.671747624874115, 'jupyter', 1), ('jupyterlab/jupyterlab', 0.669508159160614, 'jupyter', 1), ('cohere-ai/notebooks', 0.6436967253684998, 'llm', 0), ('xiaohk/stickyland', 0.6330485939979553, 'jupyter', 2), ('vizzuhq/ipyvizzu', 0.6270691156387329, 'jupyter', 2), ('ipython/ipyparallel', 0.6222683191299438, 'perf', 1), ('nteract/testbook', 0.6220455765724182, 'jupyter', 1), ('maartenbreddels/ipyvolume', 0.6165135502815247, 'jupyter', 2), ('quantopian/qgrid', 0.613193154335022, 'jupyter', 0), ('jupyterlite/jupyterlite', 0.6035483479499817, 'jupyter', 1), ('aws/graph-notebook', 0.5949639081954956, 'jupyter', 2), ('jupyter-lsp/jupyterlab-lsp', 0.5912204384803772, 'jupyter', 3), ('mamba-org/gator', 0.5904126763343811, 'jupyter', 1), ('jupyter/nbgrader', 0.5747985243797302, 'jupyter', 2), ('jakevdp/pythondatasciencehandbook', 0.5674871206283569, 'study', 1), ('bloomberg/ipydatagrid', 0.5550519824028015, 'jupyter', 0), ('jupyter-widgets/ipyleaflet', 0.5543774366378784, 'gis', 1), ('koaning/drawdata', 0.5532419085502625, 'jupyter', 1), ('nteract/papermill', 0.5524148344993591, 'jupyter', 2), ('jupyter/nbviewer', 0.547979474067688, 'jupyter', 2), ('jupyter/nbdime', 0.5463511943817139, 'jupyter', 2), ('chaoleili/jupyterlab_tensorboard', 0.5390121340751648, 'jupyter', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5353759527206421, 'study', 0), ('tkrabel/bamboolib', 0.5267034769058228, 'pandas', 1), ('ageron/handson-ml2', 0.5203615427017212, 'ml', 0)] | 645 | 8 | null | 4.96 | 244 | 177 | 107 | 0 | 31 | 75 | 31 | 244 | 362 | 90 | 1.5 | 65 |
1,304 | study | https://github.com/eugeneyan/open-llms | ['awesome'] | null | [] | [] | null | null | null | eugeneyan/open-llms | open-llms | 9,154 | 538 | 204 | null | null | 📋 A list of open LLMs available for commercial use. | eugeneyan | 2024-01-14 | 2023-05-05 | 38 | 237.325926 | null | 📋 A list of open LLMs available for commercial use. | ['commercial', 'large-language-models', 'llm', 'llms'] | ['awesome', 'commercial', 'large-language-models', 'llm', 'llms'] | 2024-01-10 | [('bentoml/openllm', 0.7019832134246826, 'ml-ops', 1), ('salesforce/xgen', 0.6812090873718262, 'llm', 2), ('mooler0410/llmspracticalguide', 0.6558331847190857, 'study', 2), ('agenta-ai/agenta', 0.6486678719520569, 'llm', 3), ('microsoft/torchscale', 0.633047878742218, 'llm', 0), ('young-geng/easylm', 0.6238888502120972, 'llm', 1), ('nat/openplayground', 0.6209505796432495, 'llm', 0), ('ibm/dromedary', 0.6077130436897278, 'llm', 0), ('confident-ai/deepeval', 0.6072402596473694, 'testing', 1), ('alpha-vllm/llama2-accessory', 0.6008363962173462, 'llm', 0), ('salesforce/codet5', 0.6007983088493347, 'nlp', 1), ('hwchase17/langchain', 0.599155068397522, 'llm', 0), ('nomic-ai/gpt4all', 0.5968722701072693, 'llm', 0), ('berriai/litellm', 0.5926091074943542, 'llm', 1), ('hegelai/prompttools', 0.5875352621078491, 'llm', 2), ('run-llama/llama-hub', 0.586604654788971, 'data', 1), ('ray-project/ray-llm', 0.5834382772445679, 'llm', 2), ('shishirpatil/gorilla', 0.5759145021438599, 'llm', 1), ('tigerlab-ai/tiger', 0.5710621476173401, 'llm', 2), ('vllm-project/vllm', 0.5680029988288879, 'llm', 1), ('hiyouga/llama-factory', 0.5650503635406494, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.5650503039360046, 'llm', 3), ('citadel-ai/langcheck', 0.5613651275634766, 'llm', 0), ('microsoft/promptflow', 0.5602272748947144, 'llm', 1), ('predibase/lorax', 0.5560584664344788, 'llm', 1), ('thudm/chatglm2-6b', 0.5501125454902649, 'llm', 2), ('langchain-ai/langsmith-cookbook', 0.5495509505271912, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5479944944381714, 'perf', 0), ('ray-project/llm-applications', 0.5464956760406494, 'llm', 1), ('bigscience-workshop/petals', 0.5463467836380005, 'data', 1), ('microsoft/semantic-kernel', 0.5385962128639221, 'llm', 1), ('deep-diver/pingpong', 0.5374715328216553, 'llm', 0), ('alphasecio/langchain-examples', 0.5366406440734863, 'llm', 1), ('microsoft/jarvis', 0.5364652276039124, 'llm', 0), ('dylanhogg/llmgraph', 0.5341588258743286, 'ml', 1), ('bobazooba/xllm', 0.5326270461082458, 'llm', 2), ('openai/evals', 0.5292133092880249, 'llm', 0), ('h2oai/h2o-llmstudio', 0.5287415385246277, 'llm', 1), ('deepset-ai/haystack', 0.5231071710586548, 'llm', 1), ('ajndkr/lanarky', 0.5215867757797241, 'llm', 0), ('nebuly-ai/nebullvm', 0.5213199257850647, 'perf', 2), ('epfllm/meditron', 0.5213027596473694, 'llm', 0), ('explosion/spacy-llm', 0.5212215185165405, 'llm', 2), ('pathwaycom/llm-app', 0.5204359889030457, 'llm', 1), ('jzhang38/tinyllama', 0.515006959438324, 'llm', 0), ('ludwig-ai/ludwig', 0.5101239681243896, 'ml-ops', 1), ('lianjiatech/belle', 0.5089041590690613, 'llm', 0), ('jerryjliu/llama_index', 0.5083422660827637, 'llm', 1), ('run-llama/llama-lab', 0.5069587826728821, 'llm', 0), ('artidoro/qlora', 0.5061990022659302, 'llm', 0), ('langchain-ai/langgraph', 0.5050806403160095, 'llm', 0), ('deep-diver/llm-as-chatbot', 0.502346932888031, 'llm', 0), ('lightning-ai/lit-gpt', 0.501139223575592, 'llm', 0), ('argilla-io/argilla', 0.5009057521820068, 'nlp', 1)] | 25 | 5 | null | 1.56 | 8 | 6 | 8 | 0 | 0 | 0 | 0 | 8 | 9 | 90 | 1.1 | 65 |
543 | ml | https://github.com/optuna/optuna | [] | null | [] | [] | null | null | null | optuna/optuna | optuna | 9,124 | 917 | 121 | Python | https://optuna.org | A hyperparameter optimization framework | optuna | 2024-01-13 | 2018-02-21 | 309 | 29.445828 | https://avatars.githubusercontent.com/u/57251745?v=4 | A hyperparameter optimization framework | ['distributed', 'hyperparameter-optimization', 'machine-learning', 'parallel'] | ['distributed', 'hyperparameter-optimization', 'machine-learning', 'parallel'] | 2024-01-10 | [('hyperopt/hyperopt', 0.7380708456039429, 'ml', 0), ('paddlepaddle/paddle', 0.6472195386886597, 'ml-dl', 1), ('kubeflow/katib', 0.6405646800994873, 'ml', 0), ('determined-ai/determined', 0.6228476166725159, 'ml-ops', 2), ('microsoft/deepspeed', 0.5794839262962341, 'ml-dl', 1), ('automl/auto-sklearn', 0.5508047938346863, 'ml', 1), ('dask/dask-ml', 0.5394331216812134, 'ml', 0), ('horovod/horovod', 0.5364230871200562, 'ml-ops', 1), ('eleutherai/oslo', 0.5354965925216675, 'ml', 0), ('uber/fiber', 0.5304052233695984, 'data', 1), ('google/vizier', 0.5277183055877686, 'ml', 2), ('alpa-projects/alpa', 0.5211974382400513, 'ml-dl', 1), ('microsoft/flaml', 0.5139668583869934, 'ml', 2), ('ray-project/ray', 0.5129156112670898, 'ml-ops', 4), ('ray-project/tune-sklearn', 0.5114966034889221, 'ml', 0), ('microsoft/nni', 0.5085669159889221, 'ml', 3), ('scikit-optimize/scikit-optimize', 0.5056672096252441, 'ml', 2)] | 255 | 3 | null | 38.81 | 208 | 166 | 72 | 0 | 7 | 10 | 7 | 208 | 407 | 90 | 2 | 65 |
1,110 | nlp | https://github.com/openai/tiktoken | ['chatgpt', 'word-segmentation', 'tokeniser'] | null | [] | [] | 1 | null | null | openai/tiktoken | tiktoken | 8,112 | 563 | 143 | Python | null | tiktoken is a fast BPE tokeniser for use with OpenAI's models. | openai | 2024-01-14 | 2022-12-01 | 60 | 133.609412 | https://avatars.githubusercontent.com/u/14957082?v=4 | tiktoken is a fast BPE tokeniser for use with OpenAI's models. | [] | ['chatgpt', 'tokeniser', 'word-segmentation'] | 2023-12-03 | [('run-llama/rags', 0.5739045143127441, 'llm', 1), ('openai/openai-cookbook', 0.5737849473953247, 'ml', 1), ('blinkdl/chatrwkv', 0.5641686320304871, 'llm', 1), ('xtekky/gpt4free', 0.5542630553245544, 'llm', 1), ('alphasecio/langchain-examples', 0.5489485263824463, 'llm', 0), ('zhudotexe/kani', 0.528551459312439, 'llm', 1), ('laion-ai/open-assistant', 0.5184189677238464, 'llm', 1), ('lm-sys/fastchat', 0.5158092975616455, 'llm', 0), ('langchain-ai/opengpts', 0.5110874176025391, 'llm', 0), ('langchain-ai/langsmith-sdk', 0.5109971761703491, 'llm', 0), ('minimaxir/gpt-2-simple', 0.5088499784469604, 'llm', 0), ('explosion/spacy-streamlit', 0.5080421566963196, 'nlp', 0), ('guardrails-ai/guardrails', 0.5039165019989014, 'llm', 0), ('shishirpatil/gorilla', 0.5037037134170532, 'llm', 1)] | 11 | 4 | null | 0.48 | 55 | 35 | 14 | 1 | 7 | 8 | 7 | 55 | 92 | 90 | 1.7 | 65 |
214 | nlp | https://github.com/speechbrain/speechbrain | [] | null | [] | [] | null | null | null | speechbrain/speechbrain | speechbrain | 7,089 | 1,212 | 123 | Python | http://speechbrain.github.io | A PyTorch-based Speech Toolkit | speechbrain | 2024-01-14 | 2020-04-28 | 196 | 36.168367 | https://avatars.githubusercontent.com/u/54749030?v=4 | A PyTorch-based Speech Toolkit | ['asr', 'audio', 'audio-processing', 'deep-learning', 'huggingface', 'language-model', 'pytorch', 'speaker-diarization', 'speaker-recognition', 'speaker-verification', 'speech-enhancement', 'speech-processing', 'speech-recognition', 'speech-separation', 'speech-to-text', 'speech-toolkit', 'speechrecognition', 'spoken-language-understanding', 'transformers', 'voice-recognition'] | ['asr', 'audio', 'audio-processing', 'deep-learning', 'huggingface', 'language-model', 'pytorch', 'speaker-diarization', 'speaker-recognition', 'speaker-verification', 'speech-enhancement', 'speech-processing', 'speech-recognition', 'speech-separation', 'speech-to-text', 'speech-toolkit', 'speechrecognition', 'spoken-language-understanding', 'transformers', 'voice-recognition'] | 2024-01-07 | [('espnet/espnet', 0.822684109210968, 'nlp', 7), ('uberi/speech_recognition', 0.6739375591278076, 'ml', 3), ('huggingface/transformers', 0.6348034739494324, 'nlp', 4), ('nvidia/nemo', 0.6236434578895569, 'nlp', 7), ('allenai/allennlp', 0.5886344313621521, 'nlp', 2), ('spotify/pedalboard', 0.5878923535346985, 'util', 2), ('nateshmbhat/pyttsx3', 0.5789477229118347, 'util', 0), ('m-bain/whisperx', 0.5771469473838806, 'nlp', 3), ('skorch-dev/skorch', 0.5581321120262146, 'ml-dl', 2), ('cmusphinx/pocketsphinx', 0.5464542508125305, 'ml', 1), ('intel/intel-extension-for-pytorch', 0.5442495942115784, 'perf', 2), ('pytorch/ignite', 0.5351871848106384, 'ml-dl', 2), ('pndurette/gtts', 0.5305692553520203, 'util', 0), ('kalliope-project/kalliope', 0.5283302664756775, 'util', 2), ('rasbt/machine-learning-book', 0.5237654447555542, 'study', 2), ('microsoft/semi-supervised-learning', 0.5235595107078552, 'ml', 2), ('rasahq/rasa', 0.5202128291130066, 'llm', 0), ('libaudioflux/audioflux', 0.5162292718887329, 'util', 3), ('pytorch/captum', 0.5150958895683289, 'ml-interpretability', 0), ('alibaba/easynlp', 0.5123403072357178, 'nlp', 3), ('blinkdl/chatrwkv', 0.5112695693969727, 'llm', 2), ('bastibe/python-soundfile', 0.5037903189659119, 'util', 0), ('deeppavlov/deeppavlov', 0.5031290054321289, 'nlp', 1), ('huggingface/huggingface_hub', 0.5026688575744629, 'ml', 2), ('huggingface/datasets', 0.5019820928573608, 'nlp', 2)] | 225 | 5 | null | 27.48 | 144 | 96 | 45 | 0 | 3 | 3 | 3 | 144 | 335 | 90 | 2.3 | 65 |
1,476 | ml | https://github.com/facebookresearch/xformers | ['transformers'] | null | [] | [] | null | null | null | facebookresearch/xformers | xformers | 6,815 | 466 | 70 | Python | https://facebookresearch.github.io/xformers/ | Hackable and optimized Transformers building blocks, supporting a composable construction. | facebookresearch | 2024-01-14 | 2021-10-13 | 119 | 56.859356 | https://avatars.githubusercontent.com/u/16943930?v=4 | Hackable and optimized Transformers building blocks, supporting a composable construction. | [] | ['transformers'] | 2024-01-05 | [('abertsch72/unlimiformer', 0.5475772023200989, 'nlp', 1)] | 71 | 3 | null | 5.54 | 92 | 29 | 27 | 0 | 13 | 15 | 13 | 92 | 239 | 90 | 2.6 | 65 |
858 | ml-ops | https://github.com/mage-ai/mage-ai | [] | null | [] | [] | 1 | null | null | mage-ai/mage-ai | mage-ai | 6,239 | 579 | 55 | Python | https://www.mage.ai/ | 🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data. | mage-ai | 2024-01-14 | 2022-05-16 | 89 | 69.988782 | https://avatars.githubusercontent.com/u/69371472?v=4 | 🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data. | ['artificial-intelligence', 'data', 'data-engineering', 'data-integration', 'data-pipelines', 'data-science', 'dbt', 'elt', 'etl', 'machine-learning', 'orchestration', 'pipeline', 'pipelines', 'reverse-etl', 'spark', 'sql', 'transformation'] | ['artificial-intelligence', 'data', 'data-engineering', 'data-integration', 'data-pipelines', 'data-science', 'dbt', 'elt', 'etl', 'machine-learning', 'orchestration', 'pipeline', 'pipelines', 'reverse-etl', 'spark', 'sql', 'transformation'] | 2024-01-14 | [('airbytehq/airbyte', 0.7392861247062683, 'data', 6), ('orchest/orchest', 0.7309496402740479, 'ml-ops', 5), ('ploomber/ploomber', 0.7089954614639282, 'ml-ops', 4), ('kestra-io/kestra', 0.6831650137901306, 'ml-ops', 8), ('dagster-io/dagster', 0.6750965714454651, 'ml-ops', 6), ('flyteorg/flyte', 0.6692841053009033, 'ml-ops', 3), ('meltano/meltano', 0.6557142734527588, 'ml-ops', 5), ('apache/airflow', 0.6510021090507507, 'ml-ops', 8), ('astronomer/astro-sdk', 0.6467173099517822, 'ml-ops', 4), ('linealabs/lineapy', 0.6465555429458618, 'jupyter', 0), ('avaiga/taipy', 0.6288012266159058, 'data', 4), ('kubeflow/pipelines', 0.622243344783783, 'ml-ops', 3), ('dagworks-inc/hamilton', 0.6080176830291748, 'ml-ops', 5), ('dgarnitz/vectorflow', 0.6055392622947693, 'data', 2), ('hi-primus/optimus', 0.5950447916984558, 'ml-ops', 3), ('netflix/metaflow', 0.5949897766113281, 'ml-ops', 2), ('featureform/embeddinghub', 0.5914458632469177, 'nlp', 2), ('prefecthq/prefect', 0.5904417037963867, 'ml-ops', 5), ('bodywork-ml/bodywork-core', 0.5791720151901245, 'ml-ops', 4), ('dbt-labs/dbt-core', 0.5732520818710327, 'ml-ops', 1), ('polyaxon/polyaxon', 0.5694826245307922, 'ml-ops', 4), ('fugue-project/fugue', 0.5678737163543701, 'pandas', 3), ('pathwaycom/pathway', 0.5671728849411011, 'data', 0), ('streamlit/streamlit', 0.5670653581619263, 'viz', 2), ('apache/spark', 0.5627126693725586, 'data', 2), ('great-expectations/great_expectations', 0.5621156692504883, 'ml-ops', 3), ('polyaxon/datatile', 0.5572016835212708, 'pandas', 2), ('superduperdb/superduperdb', 0.5560696125030518, 'data', 1), ('getindata/kedro-kubeflow', 0.5537773370742798, 'ml-ops', 0), ('pydoit/doit', 0.551956057548523, 'util', 1), ('feast-dev/feast', 0.5513089299201965, 'ml-ops', 3), ('whylabs/whylogs', 0.5448665022850037, 'util', 2), ('allegroai/clearml', 0.5418257713317871, 'ml-ops', 1), ('kubeflow-kale/kale', 0.5401076674461365, 'ml-ops', 1), ('huggingface/datasets', 0.5363893508911133, 'nlp', 1), ('merantix-momentum/squirrel-core', 0.5338592529296875, 'ml', 2), ('zenml-io/zenml', 0.5322885513305664, 'ml-ops', 3), ('mlflow/mlflow', 0.5320558547973633, 'ml-ops', 1), ('google/ml-metadata', 0.524271547794342, 'ml-ops', 0), ('prefecthq/server', 0.5205321311950684, 'util', 1), ('simonw/datasette', 0.5153981447219849, 'data', 1), ('kedro-org/kedro', 0.5148924589157104, 'ml-ops', 2), ('databrickslabs/dbx', 0.5128315091133118, 'data', 0), ('onnx/onnx', 0.5106418132781982, 'ml', 1), ('google/mediapipe', 0.508601188659668, 'ml', 1), ('tobymao/sqlglot', 0.5064417123794556, 'data', 2)] | 82 | 1 | null | 48.85 | 641 | 541 | 20 | 0 | 43 | 27 | 43 | 640 | 372 | 90 | 0.6 | 65 |
1,562 | llm | https://github.com/jzhang38/tinyllama | ['llama', 'language-model'] | null | [] | [] | null | null | null | jzhang38/tinyllama | TinyLlama | 5,287 | 264 | 110 | Python | null | The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens. | jzhang38 | 2024-01-14 | 2023-09-02 | 21 | 246.726667 | null | The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens. | [] | ['language-model', 'llama'] | 2024-01-10 | [('microsoft/llama-2-onnx', 0.7340604066848755, 'llm', 2), ('facebookresearch/llama-recipes', 0.6900231242179871, 'llm', 2), ('lightning-ai/lit-llama', 0.6785302758216858, 'llm', 2), ('tloen/alpaca-lora', 0.6666224598884583, 'llm', 2), ('zrrskywalker/llama-adapter', 0.6362742185592651, 'llm', 2), ('run-llama/llama-lab', 0.6213663816452026, 'llm', 2), ('facebookresearch/llama', 0.6092095375061035, 'llm', 2), ('young-geng/easylm', 0.597965657711029, 'llm', 2), ('bigscience-workshop/petals', 0.588677167892456, 'data', 1), ('mshumer/gpt-llm-trainer', 0.5883111953735352, 'llm', 0), ('facebookresearch/codellama', 0.5828747749328613, 'llm', 2), ('openlm-research/open_llama', 0.5819482207298279, 'llm', 2), ('cg123/mergekit', 0.5811179876327515, 'llm', 1), ('salesforce/xgen', 0.57785564661026, 'llm', 1), ('ggerganov/llama.cpp', 0.5698243379592896, 'llm', 2), ('karpathy/llama2.c', 0.5350930094718933, 'llm', 2), ('tairov/llama2.mojo', 0.5322071313858032, 'llm', 1), ('bobazooba/xllm', 0.5300989151000977, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5206746459007263, 'perf', 0), ('predibase/lorax', 0.5169039964675903, 'llm', 1), ('run-llama/llama-hub', 0.5164508819580078, 'data', 0), ('titanml/takeoff', 0.5162729620933533, 'llm', 2), ('eugeneyan/open-llms', 0.515006959438324, 'study', 0), ('abetlen/llama-cpp-python', 0.5099416375160217, 'llm', 2), ('huawei-noah/pretrained-language-model', 0.5081942081451416, 'nlp', 0), ('hiyouga/llama-factory', 0.5053484439849854, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.505348265171051, 'llm', 2), ('sjtu-ipads/powerinfer', 0.5038610696792603, 'llm', 1)] | 8 | 2 | null | 2.19 | 93 | 80 | 4 | 0 | 0 | 0 | 0 | 93 | 143 | 90 | 1.5 | 65 |
821 | ml-rl | https://github.com/farama-foundation/gymnasium | [] | null | [] | [] | null | null | null | farama-foundation/gymnasium | Gymnasium | 4,727 | 568 | 36 | Python | https://gymnasium.farama.org | An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym) | farama-foundation | 2024-01-14 | 2022-09-08 | 72 | 65.007859 | https://avatars.githubusercontent.com/u/62961550?v=4 | An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym) | ['api', 'gym', 'reinforcement-learning'] | ['api', 'gym', 'reinforcement-learning'] | 2024-01-13 | [('pettingzoo-team/pettingzoo', 0.947864830493927, 'ml-rl', 3), ('nvidia-omniverse/isaacgymenvs', 0.6873985528945923, 'sim', 1), ('unity-technologies/ml-agents', 0.6212126612663269, 'ml-rl', 1), ('pytorch/rl', 0.6115036010742188, 'ml-rl', 1), ('nvidia-omniverse/omniisaacgymenvs', 0.6047082543373108, 'sim', 0), ('google/dopamine', 0.5846539735794067, 'ml-rl', 0), ('openai/baselines', 0.5754907131195068, 'ml-rl', 0), ('thu-ml/tianshou', 0.57296222448349, 'ml-rl', 0), ('deepmind/acme', 0.5646693110466003, 'ml-rl', 1), ('facebookresearch/reagent', 0.5644688606262207, 'ml-rl', 0), ('humancompatibleai/imitation', 0.5637737512588501, 'ml-rl', 0), ('facebookresearch/habitat-lab', 0.5635895729064941, 'sim', 1), ('inspirai/timechamber', 0.5623535513877869, 'sim', 1), ('kzl/decision-transformer', 0.5532186031341553, 'ml-rl', 1), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5474168062210083, 'study', 1), ('huggingface/deep-rl-class', 0.5383160710334778, 'study', 1), ('openai/gym', 0.533967137336731, 'ml-rl', 1), ('openai/spinningup', 0.5327202081680298, 'study', 0), ('deepmind/pysc2', 0.5224155187606812, 'ml-rl', 1), ('operand/agency', 0.5203875303268433, 'llm', 1), ('tensorlayer/tensorlayer', 0.5202954411506653, 'ml-rl', 1), ('salesforce/warp-drive', 0.5065247416496277, 'ml-rl', 1), ('ai4finance-foundation/finrl', 0.5031803250312805, 'finance', 1)] | 459 | 2 | null | 4.96 | 171 | 134 | 16 | 0 | 5 | 8 | 5 | 171 | 315 | 90 | 1.8 | 65 |
1,854 | gui | https://github.com/samuelcolvin/fastui | [] | FastUI is a new way to build web application user interfaces defined by declarative Python code. | [] | [] | null | null | null | samuelcolvin/fastui | FastUI | 3,211 | 273 | 28 | TypeScript | https://fastui-demo.onrender.com | Build better UIs faster. | samuelcolvin | 2024-01-14 | 2023-09-18 | 19 | 167.738806 | https://avatars.githubusercontent.com/u/110818415?v=4 | Build better UIs faster. | ['fastapi', 'pydantic', 'react'] | ['fastapi', 'pydantic', 'react'] | 2023-12-29 | [('fastai/fastcore', 0.546245813369751, 'util', 0), ('dmontagu/fastapi_client', 0.5091067552566528, 'web', 0)] | 18 | 3 | null | 1.96 | 151 | 95 | 4 | 1 | 2 | 6 | 2 | 151 | 281 | 90 | 1.9 | 65 |
26 | term | https://github.com/google/python-fire | [] | null | [] | [] | null | null | null | google/python-fire | python-fire | 25,802 | 1,487 | 375 | Python | null | Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object. | google | 2024-01-14 | 2017-02-21 | 362 | 71.276243 | https://avatars.githubusercontent.com/u/1342004?v=4 | Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object. | ['cli'] | ['cli'] | 2024-01-09 | [('python-poetry/cleo', 0.6746692657470703, 'term', 1), ('kellyjonbrazil/jc', 0.6432965397834778, 'util', 1), ('pyscript/pyscript-cli', 0.6401512026786804, 'web', 0), ('urwid/urwid', 0.6262136101722717, 'term', 0), ('pallets/click', 0.6196329593658447, 'term', 1), ('tiangolo/typer', 0.6071035265922546, 'term', 1), ('jquast/blessed', 0.5881098508834839, 'term', 1), ('pexpect/pexpect', 0.5853911638259888, 'util', 0), ('pytoolz/toolz', 0.5839331150054932, 'util', 0), ('hoffstadt/dearpygui', 0.5763037800788879, 'gui', 0), ('prompt-toolkit/ptpython', 0.5544407367706299, 'util', 1), ('hugovk/pypistats', 0.5451176166534424, 'util', 1), ('tmbo/questionary', 0.5444633960723877, 'term', 1), ('kellyjonbrazil/jello', 0.5335484743118286, 'util', 1), ('pypy/pypy', 0.5175889730453491, 'util', 0), ('pypa/hatch', 0.5173959732055664, 'util', 1), ('samuelcolvin/python-devtools', 0.5147319436073303, 'debug', 0), ('landscapeio/prospector', 0.5145845413208008, 'util', 0), ('python/cpython', 0.5122049450874329, 'util', 0), ('beeware/toga', 0.5118656754493713, 'gui', 0), ('hhatto/autopep8', 0.5113070011138916, 'util', 0), ('xonsh/xonsh', 0.5076464414596558, 'util', 1), ('getsentry/responses', 0.5072945952415466, 'testing', 0), ('pygamelib/pygamelib', 0.5067519545555115, 'gamedev', 0), ('willmcgugan/textual', 0.5056248307228088, 'term', 1), ('pdm-project/pdm', 0.5054830312728882, 'util', 0), ('pympler/pympler', 0.5053215622901917, 'perf', 0), ('nedbat/coveragepy', 0.5045384764671326, 'testing', 0), ('omry/omegaconf', 0.5032675862312317, 'util', 0)] | 63 | 4 | null | 0.25 | 34 | 13 | 84 | 0 | 0 | 2 | 2 | 34 | 74 | 90 | 2.2 | 64 |
1,056 | study | https://github.com/d2l-ai/d2l-en | [] | null | [] | [] | null | null | null | d2l-ai/d2l-en | d2l-en | 20,540 | 4,016 | 394 | Python | https://D2L.ai | Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. | d2l-ai | 2024-01-14 | 2018-10-09 | 277 | 74.151625 | https://avatars.githubusercontent.com/u/43974506?v=4 | Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. | ['book', 'computer-vision', 'data-science', 'deep-learning', 'gaussian-processes', 'hyperparameter-optimization', 'jax', 'kaggle', 'keras', 'machine-learning', 'mxnet', 'natural-language-processing', 'notebook', 'pytorch', 'recommender-system', 'reinforcement-learning', 'tensorflow'] | ['book', 'computer-vision', 'data-science', 'deep-learning', 'gaussian-processes', 'hyperparameter-optimization', 'jax', 'kaggle', 'keras', 'machine-learning', 'mxnet', 'natural-language-processing', 'notebook', 'pytorch', 'recommender-system', 'reinforcement-learning', 'tensorflow'] | 2023-12-11 | [('tensorlayer/tensorlayer', 0.6486682891845703, 'ml-rl', 3), ('keras-team/keras', 0.6172467470169067, 'ml-dl', 6), ('mrdbourke/pytorch-deep-learning', 0.6161856055259705, 'study', 3), ('tensorflow/tensor2tensor', 0.5922254920005798, 'ml', 3), ('nvidia/deeplearningexamples', 0.5897380709648132, 'ml-dl', 5), ('google/trax', 0.587719202041626, 'ml-dl', 4), ('ageron/handson-ml2', 0.5854299664497375, 'ml', 0), ('tensorflow/tensorflow', 0.5832685828208923, 'ml-dl', 3), ('explosion/thinc', 0.5795356035232544, 'ml-dl', 7), ('keras-rl/keras-rl', 0.5773378610610962, 'ml-rl', 4), ('fchollet/deep-learning-with-python-notebooks', 0.5766072273254395, 'study', 0), ('udlbook/udlbook', 0.573790431022644, 'study', 2), ('mrdbourke/tensorflow-deep-learning', 0.5674564242362976, 'study', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5661432147026062, 'study', 2), ('horovod/horovod', 0.5628776550292969, 'ml-ops', 6), ('xl0/lovely-tensors', 0.5590056777000427, 'ml-dl', 2), ('udacity/deep-learning-v2-pytorch', 0.5573995113372803, 'study', 2), ('ggerganov/ggml', 0.5564393997192383, 'ml', 1), ('probml/pyprobml', 0.5489851236343384, 'ml', 4), ('huggingface/transformers', 0.5483046174049377, 'nlp', 6), ('deepmodeling/deepmd-kit', 0.5467190146446228, 'sim', 2), ('christoschristofidis/awesome-deep-learning', 0.5462198853492737, 'study', 2), ('microsoft/onnxruntime', 0.5409604907035828, 'ml', 4), ('davidadsp/generative_deep_learning_2nd_edition', 0.5406649708747864, 'study', 4), ('salesforce/warp-drive', 0.5405166745185852, 'ml-rl', 3), ('pytorch/ignite', 0.54007488489151, 'ml-dl', 3), ('keras-team/autokeras', 0.5389357805252075, 'ml-dl', 4), ('rasbt/machine-learning-book', 0.5370543003082275, 'study', 3), ('rasbt/stat453-deep-learning-ss20', 0.5362268090248108, 'study', 0), ('atcold/nyu-dlsp21', 0.5323129296302795, 'study', 1), ('graykode/nlp-tutorial', 0.5312547087669373, 'study', 3), ('google/tf-quant-finance', 0.5287189483642578, 'finance', 1), ('openai/spinningup', 0.5276309251785278, 'study', 0), ('rafiqhasan/auto-tensorflow', 0.5260531306266785, 'ml-dl', 2), ('tatsu-lab/stanford_alpaca', 0.5226318836212158, 'llm', 1), ('denys88/rl_games', 0.5216466188430786, 'ml-rl', 3), ('tensorly/tensorly', 0.5216432213783264, 'ml-dl', 5), ('firmai/industry-machine-learning', 0.5169808268547058, 'study', 2), ('thu-ml/tianshou', 0.5155929923057556, 'ml-rl', 1), ('deepmind/dm-haiku', 0.5113567113876343, 'ml-dl', 3), ('mrdbourke/zero-to-mastery-ml', 0.5092582702636719, 'study', 3), ('tlkh/tf-metal-experiments', 0.508011519908905, 'perf', 2), ('pytorch/pytorch', 0.5062558650970459, 'ml-dl', 2), ('adap/flower', 0.505675733089447, 'ml-ops', 4), ('pytorch/rl', 0.5053571462631226, 'ml-rl', 3), ('microsoft/deepspeed', 0.5029295682907104, 'ml-dl', 3), ('whitead/dmol-book', 0.5019837021827698, 'ml-dl', 1), ('optimalscale/lmflow', 0.5011979341506958, 'llm', 2), ('determined-ai/determined', 0.5009527802467346, 'ml-ops', 7)] | 319 | 7 | null | 4.15 | 36 | 7 | 64 | 1 | 1 | 6 | 1 | 36 | 27 | 90 | 0.8 | 64 |
468 | nlp | https://github.com/microsoft/unilm | [] | null | [] | [] | null | null | null | microsoft/unilm | unilm | 16,868 | 2,249 | 278 | Python | https://aka.ms/GeneralAI | Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities | microsoft | 2024-01-14 | 2019-07-23 | 236 | 71.474576 | https://avatars.githubusercontent.com/u/6154722?v=4 | Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities | ['beit', 'beit-3', 'deepnet', 'document-ai', 'foundation-models', 'kosmos', 'kosmos-1', 'layoutlm', 'layoutxlm', 'llm', 'minilm', 'mllm', 'multimodal', 'nlp', 'pre-trained-model', 'textdiffuser', 'trocr', 'unilm', 'xlm-e'] | ['beit', 'beit-3', 'deepnet', 'document-ai', 'foundation-models', 'kosmos', 'kosmos-1', 'layoutlm', 'layoutxlm', 'llm', 'minilm', 'mllm', 'multimodal', 'nlp', 'pre-trained-model', 'textdiffuser', 'trocr', 'unilm', 'xlm-e'] | 2024-01-11 | [('qanastek/drbert', 0.5781573057174683, 'llm', 1), ('yueyu1030/attrprompt', 0.5726070404052734, 'llm', 0), ('google-research/electra', 0.5669850707054138, 'ml-dl', 1), ('ofa-sys/ofa', 0.5649746060371399, 'llm', 1), ('openai/finetune-transformer-lm', 0.5644842982292175, 'llm', 0), ('openai/clip', 0.5614645481109619, 'ml-dl', 0), ('rasahq/rasa', 0.5554572939872742, 'llm', 1), ('thudm/glm-130b', 0.5527222156524658, 'llm', 0), ('young-geng/easylm', 0.5508254170417786, 'llm', 0), ('deepset-ai/farm', 0.5462345480918884, 'nlp', 1), ('huawei-noah/pretrained-language-model', 0.5461228489875793, 'nlp', 0), ('explosion/spacy-llm', 0.5390931367874146, 'llm', 2), ('alibaba/easynlp', 0.5370928645133972, 'nlp', 1), ('optimalscale/lmflow', 0.5366694331169128, 'llm', 0), ('lm-sys/fastchat', 0.5365498661994934, 'llm', 0), ('chandlerbang/awesome-self-supervised-gnn', 0.5360260605812073, 'study', 0), ('infinitylogesh/mutate', 0.5307291746139526, 'nlp', 0), ('next-gpt/next-gpt', 0.5269091129302979, 'llm', 3), ('huggingface/datasets', 0.5208196043968201, 'nlp', 1), ('cg123/mergekit', 0.5200158357620239, 'llm', 1), ('llmware-ai/llmware', 0.5189810991287231, 'llm', 1), ('salesforce/blip', 0.5181792378425598, 'diffusion', 0), ('databrickslabs/dolly', 0.5165247917175293, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5151917338371277, 'llm', 2), ('minimaxir/textgenrnn', 0.5143858194351196, 'nlp', 0), ('thudm/p-tuning-v2', 0.5134304761886597, 'nlp', 0), ('tatsu-lab/stanford_alpaca', 0.511536180973053, 'llm', 0), ('extreme-bert/extreme-bert', 0.5103119015693665, 'llm', 1), ('argilla-io/argilla', 0.5100960731506348, 'nlp', 2), ('togethercomputer/redpajama-data', 0.5096539855003357, 'llm', 0), ('huggingface/autotrain-advanced', 0.5079038143157959, 'ml', 0), ('microsoft/lmops', 0.5072470903396606, 'llm', 2), ('huggingface/text-generation-inference', 0.5068984627723694, 'llm', 1), ('bigscience-workshop/biomedical', 0.5054998397827148, 'data', 0), ('jbesomi/texthero', 0.5031306147575378, 'nlp', 1), ('nvidia/deeplearningexamples', 0.5029410719871521, 'ml-dl', 1), ('bigscience-workshop/petals', 0.502390444278717, 'data', 1), ('mooler0410/llmspracticalguide', 0.5018056631088257, 'study', 1), ('openbmb/toolbench', 0.5009614825248718, 'llm', 0)] | 64 | 4 | null | 3.52 | 133 | 43 | 55 | 0 | 0 | 1 | 1 | 133 | 192 | 90 | 1.4 | 64 |
1,690 | util | https://github.com/rustpython/rustpython | ['rust'] | null | [] | [] | null | null | null | rustpython/rustpython | RustPython | 16,107 | 1,153 | 161 | Rust | https://rustpython.github.io | A Python Interpreter written in Rust | rustpython | 2024-01-14 | 2018-05-28 | 296 | 54.389291 | https://avatars.githubusercontent.com/u/39710557?v=4 | A Python Interpreter written in Rust | ['compiler', 'interpreter', 'jit', 'language', 'python-language', 'rust', 'wasm'] | ['compiler', 'interpreter', 'jit', 'language', 'python-language', 'rust', 'wasm'] | 2024-01-12 | [('pyo3/pyo3', 0.6475306749343872, 'util', 1), ('numba/llvmlite', 0.638462483882904, 'util', 0), ('aswinnnn/pyscan', 0.6372954249382019, 'security', 1), ('pyo3/maturin', 0.6316028237342834, 'util', 1), ('astral-sh/ruff', 0.6286622881889343, 'util', 1), ('python/cpython', 0.5933462977409363, 'util', 0), ('pyo3/rust-numpy', 0.5917856097221375, 'util', 1), ('pypy/pypy', 0.5846704244613647, 'util', 1), ('facebookincubator/cinder', 0.5831960439682007, 'perf', 3), ('samuelcolvin/rtoml', 0.5515300035476685, 'data', 1), ('pyston/pyston', 0.543964684009552, 'util', 0), ('cython/cython', 0.5352054238319397, 'util', 0), ('exaloop/codon', 0.5343741774559021, 'perf', 1), ('brandtbucher/specialist', 0.5334833860397339, 'perf', 0), ('pola-rs/polars', 0.5321800112724304, 'pandas', 1), ('pytoolz/toolz', 0.5320417881011963, 'util', 0), ('delta-io/delta-rs', 0.5259521007537842, 'pandas', 1), ('eventual-inc/daft', 0.5145300626754761, 'pandas', 1), ('fastai/fastcore', 0.5066707134246826, 'util', 0), ('mdmzfzl/neetcode-solutions', 0.5018560886383057, 'study', 1)] | 404 | 2 | null | 20.56 | 69 | 44 | 69 | 0 | 0 | 1 | 1 | 68 | 100 | 90 | 1.5 | 64 |
808 | ml-dl | https://github.com/danielgatis/rembg | [] | null | [] | [] | null | null | null | danielgatis/rembg | rembg | 12,793 | 1,537 | 136 | Python | null | Rembg is a tool to remove images background | danielgatis | 2024-01-14 | 2020-08-10 | 181 | 70.623817 | null | Rembg is a tool to remove images background | ['background-removal', 'image-processing'] | ['background-removal', 'image-processing'] | 2023-12-16 | [] | 48 | 5 | null | 1.81 | 55 | 44 | 42 | 1 | 22 | 16 | 22 | 55 | 73 | 90 | 1.3 | 64 |
237 | data | https://github.com/tiangolo/sqlmodel | [] | null | [] | [] | 1 | null | null | tiangolo/sqlmodel | sqlmodel | 11,999 | 554 | 151 | Python | https://sqlmodel.tiangolo.com/ | SQL databases in Python, designed for simplicity, compatibility, and robustness. | tiangolo | 2024-01-14 | 2021-08-24 | 127 | 94.480315 | null | SQL databases in Python, designed for simplicity, compatibility, and robustness. | ['fastapi', 'json', 'json-schema', 'pydantic', 'sql', 'sqlalchemy'] | ['fastapi', 'json', 'json-schema', 'pydantic', 'sql', 'sqlalchemy'] | 2024-01-09 | [('ibis-project/ibis', 0.8095237612724304, 'data', 2), ('sqlalchemy/sqlalchemy', 0.8052466511726379, 'data', 2), ('mcfunley/pugsql', 0.6844363808631897, 'data', 1), ('andialbrecht/sqlparse', 0.6739121079444885, 'data', 0), ('tobymao/sqlglot', 0.6654618382453918, 'data', 1), ('collerek/ormar', 0.6308665871620178, 'data', 3), ('sqlalchemy/alembic', 0.6223205924034119, 'data', 2), ('kayak/pypika', 0.6139056086540222, 'data', 1), ('macbre/sql-metadata', 0.6107516288757324, 'data', 1), ('malloydata/malloy-py', 0.6022137403488159, 'data', 1), ('simonw/sqlite-utils', 0.5946550965309143, 'data', 0), ('falconry/falcon', 0.5907256007194519, 'web', 0), ('aminalaee/sqladmin', 0.5850541591644287, 'data', 2), ('plotly/dash', 0.5841458439826965, 'viz', 0), ('coleifer/peewee', 0.5841237306594849, 'data', 0), ('aio-libs/aiomysql', 0.5758809447288513, 'data', 1), ('machow/siuba', 0.5724479556083679, 'pandas', 1), ('python-odin/odin', 0.5694354176521301, 'util', 1), ('tconbeer/harlequin', 0.569147527217865, 'term', 1), ('krzjoa/awesome-python-data-science', 0.5662049651145935, 'study', 0), ('rawheel/fastapi-boilerplate', 0.5594669580459595, 'web', 3), ('datafold/data-diff', 0.5563005805015564, 'data', 1), ('nasdaq/data-link-python', 0.5559763312339783, 'finance', 0), ('fastai/fastcore', 0.5534236431121826, 'util', 0), ('tiangolo/fastapi', 0.5522589683532715, 'web', 4), ('strawberry-graphql/strawberry', 0.5469264984130859, 'web', 0), ('aio-libs/aiopg', 0.546112596988678, 'data', 1), ('agronholm/sqlacodegen', 0.542255163192749, 'data', 0), ('simonw/datasette', 0.5402882695198059, 'data', 2), ('marshmallow-code/marshmallow', 0.539881706237793, 'util', 0), ('aeternalis-ingenium/fastapi-backend-template', 0.5365174412727356, 'web', 2), ('pandas-dev/pandas', 0.5365090370178223, 'pandas', 0), ('willmcgugan/textual', 0.5339970588684082, 'term', 0), ('1200wd/bitcoinlib', 0.5315213799476624, 'crypto', 0), ('pytoolz/toolz', 0.5314618945121765, 'util', 0), ('sfu-db/connector-x', 0.5301145911216736, 'data', 1), ('mause/duckdb_engine', 0.529965877532959, 'data', 2), ('piccolo-orm/piccolo_admin', 0.5287275910377502, 'data', 1), ('aws/aws-sdk-pandas', 0.5277955532073975, 'pandas', 0), ('eleutherai/pyfra', 0.5258613228797913, 'ml', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5256924629211426, 'template', 3), ('jsonpickle/jsonpickle', 0.5255077481269836, 'data', 1), ('pytables/pytables', 0.5233675241470337, 'data', 0), ('jazzband/tablib', 0.5218853950500488, 'data', 0), ('jina-ai/vectordb', 0.52092444896698, 'data', 0), ('pyston/pyston', 0.5203248858451843, 'util', 0), ('fugue-project/fugue', 0.5192634463310242, 'pandas', 1), ('bottlepy/bottle', 0.5186842679977417, 'web', 0), ('s3rius/fastapi-template', 0.5149979591369629, 'web', 1), ('saulpw/visidata', 0.513899564743042, 'term', 1), ('pydantic/pydantic', 0.5132742524147034, 'util', 2), ('keon/algorithms', 0.5121207237243652, 'util', 0), ('kellyjonbrazil/jello', 0.5081574320793152, 'util', 1), ('python-cachier/cachier', 0.5081299543380737, 'perf', 0), ('pyparsing/pyparsing', 0.5065826773643494, 'util', 0), ('pypy/pypy', 0.5045502185821533, 'util', 0), ('lk-geimfari/mimesis', 0.5006476640701294, 'data', 1)] | 71 | 1 | null | 1.44 | 170 | 105 | 29 | 0 | 5 | 5 | 5 | 170 | 264 | 90 | 1.6 | 64 |
88 | math | https://github.com/sympy/sympy | [] | null | [] | [] | 1 | null | null | sympy/sympy | sympy | 11,751 | 4,180 | 291 | Python | https://sympy.org/ | A computer algebra system written in pure Python | sympy | 2024-01-14 | 2010-04-30 | 717 | 16.37607 | https://avatars.githubusercontent.com/u/260832?v=4 | A computer algebra system written in pure Python | ['computer-algebra', 'math', 'science'] | ['computer-algebra', 'math', 'science'] | 2024-01-14 | [('pyston/pyston', 0.6676157712936401, 'util', 0), ('python/cpython', 0.6439580321311951, 'util', 0), ('scipy/scipy', 0.6143859028816223, 'math', 0), ('fredrik-johansson/mpmath', 0.6130483150482178, 'math', 0), ('artemyk/dynpy', 0.6068984270095825, 'sim', 0), ('pyomo/pyomo', 0.5923652052879333, 'math', 0), ('pytoolz/toolz', 0.5918540358543396, 'util', 0), ('gbeced/pyalgotrade', 0.5751481652259827, 'finance', 0), ('norvig/pytudes', 0.5708892941474915, 'util', 0), ('pypy/pypy', 0.5672004222869873, 'util', 0), ('numpy/numpy', 0.5636308193206787, 'math', 0), ('google/latexify_py', 0.5628668069839478, 'util', 0), ('joblib/joblib', 0.5607999563217163, 'util', 0), ('connorferster/handcalcs', 0.5598889589309692, 'jupyter', 0), ('eleutherai/pyfra', 0.5521600246429443, 'ml', 0), ('thealgorithms/python', 0.5507904887199402, 'study', 0), ('has2k1/plotnine', 0.5483768582344055, 'viz', 0), ('mynameisfiber/high_performance_python_2e', 0.5473185777664185, 'study', 0), ('scikit-geometry/scikit-geometry', 0.5399286150932312, 'gis', 0), ('scikit-learn/scikit-learn', 0.5355417132377625, 'ml', 0), ('hgrecco/pint', 0.534096896648407, 'util', 1), ('adafruit/circuitpython', 0.5332902669906616, 'util', 0), ('keon/algorithms', 0.5286232233047485, 'util', 0), ('pytransitions/transitions', 0.523476243019104, 'util', 0), ('rasbt/mlxtend', 0.5225716829299927, 'ml', 0), ('pyparsing/pyparsing', 0.521645188331604, 'util', 0), ('quantopian/zipline', 0.5198596119880676, 'finance', 0), ('pyca/cryptography', 0.518089234828949, 'util', 0), ('probml/pyprobml', 0.5161436200141907, 'ml', 0), ('pymc-devs/pymc3', 0.5158290863037109, 'ml', 0), ('legrandin/pycryptodome', 0.5150558352470398, 'util', 0), ('google/pyglove', 0.5143080353736877, 'util', 0), ('julienpalard/pipe', 0.5134634971618652, 'util', 0), ('brandon-rhodes/python-patterns', 0.5133131742477417, 'util', 0), ('scikit-mobility/scikit-mobility', 0.5121610164642334, 'gis', 0), ('wesm/pydata-book', 0.511038601398468, 'study', 0), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5073643326759338, 'study', 0), ('ipython/ipyparallel', 0.5034547448158264, 'perf', 0), ('ljvmiranda921/seagull', 0.5007748603820801, 'sim', 0)] | 1,267 | 3 | null | 71.48 | 446 | 259 | 167 | 0 | 2 | 6 | 2 | 449 | 1,316 | 90 | 2.9 | 64 |
1,523 | llm | https://github.com/smol-ai/developer | ['ai', 'coding-assistant', 'autonomous-agent'] | null | [] | [] | 1 | null | null | smol-ai/developer | developer | 11,435 | 1,120 | 154 | Python | https://twitter.com/SmolModels | the first library to let you embed a developer agent in your own app! | smol-ai | 2024-01-12 | 2023-05-13 | 37 | 305.515267 | https://avatars.githubusercontent.com/u/132172705?v=4 | the first library to let you embed a developer agent in your own app! | [] | ['ai', 'autonomous-agent', 'coding-assistant'] | 2023-09-25 | [('antonosika/gpt-engineer', 0.6368786096572876, 'llm', 3), ('prefecthq/marvin', 0.6331506967544556, 'nlp', 1), ('sweepai/sweep', 0.5850329995155334, 'llm', 1), ('transformeroptimus/superagi', 0.5681149363517761, 'llm', 1), ('pythagora-io/gpt-pilot', 0.5505355000495911, 'llm', 2), ('lastmile-ai/aiconfig', 0.5501940846443176, 'util', 1), ('cheshire-cat-ai/core', 0.5464283227920532, 'llm', 1), ('operand/agency', 0.5302104949951172, 'llm', 2), ('krohling/bondai', 0.5269186496734619, 'llm', 0), ('mlc-ai/mlc-llm', 0.5239886045455933, 'llm', 0), ('microsoft/semantic-kernel', 0.5124703049659729, 'llm', 1), ('facebookresearch/habitat-lab', 0.5017600059509277, 'sim', 1)] | 21 | 9 | null | 1.79 | 7 | 1 | 8 | 4 | 0 | 0 | 0 | 7 | 3 | 90 | 0.4 | 64 |
751 | diffusion | https://github.com/divamgupta/diffusionbee-stable-diffusion-ui | [] | null | [] | [] | null | null | null | divamgupta/diffusionbee-stable-diffusion-ui | diffusionbee-stable-diffusion-ui | 11,411 | 558 | 92 | JavaScript | https://diffusionbee.com | Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed. | divamgupta | 2024-01-14 | 2022-09-06 | 73 | 156.315068 | null | Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed. | ['electron-app', 'macos', 'stable-diffusion'] | ['electron-app', 'macos', 'stable-diffusion'] | 2023-12-28 | [('apple/ml-stable-diffusion', 0.5508177876472473, 'diffusion', 0), ('comfyanonymous/comfyui', 0.5425298810005188, 'diffusion', 1), ('carson-katri/dream-textures', 0.534104585647583, 'diffusion', 1), ('bentoml/onediffusion', 0.5153639316558838, 'diffusion', 1)] | 18 | 3 | null | 0.54 | 36 | 5 | 16 | 1 | 6 | 16 | 6 | 36 | 51 | 90 | 1.4 | 64 |
73 | util | https://github.com/python-pillow/pillow | [] | null | [] | [] | null | null | null | python-pillow/pillow | Pillow | 11,402 | 2,157 | 223 | Python | https://python-pillow.org | Python Imaging Library (Fork) | python-pillow | 2024-01-13 | 2012-07-24 | 601 | 18.971714 | https://avatars.githubusercontent.com/u/2036701?v=4 | Python Imaging Library (Fork) | ['c', 'cross-platform', 'image', 'image-processing', 'pil', 'pillow'] | ['c', 'cross-platform', 'image', 'image-processing', 'pil', 'pillow'] | 2024-01-12 | [('imageio/imageio', 0.6861987113952637, 'util', 0), ('scikit-image/scikit-image', 0.6156206130981445, 'util', 1), ('rhettbull/osxphotos', 0.5487352609634399, 'util', 0), ('lightly-ai/lightly', 0.5426392555236816, 'ml', 0), ('mdbloice/augmentor', 0.5397363305091858, 'ml', 0), ('luispedro/mahotas', 0.5384292602539062, 'viz', 0), ('scitools/cartopy', 0.5182700157165527, 'gis', 0), ('pypy/pypy', 0.5135209560394287, 'util', 0), ('pyglet/pyglet', 0.505748450756073, 'gamedev', 0), ('radiantearth/radiant-mlhub', 0.5047886967658997, 'gis', 0)] | 458 | 4 | null | 35.9 | 305 | 269 | 140 | 0 | 5 | 8 | 5 | 305 | 743 | 90 | 2.4 | 64 |
393 | web | https://github.com/encode/starlette | [] | null | [] | [] | null | null | null | encode/starlette | starlette | 9,054 | 805 | 105 | Python | https://www.starlette.io/ | The little ASGI framework that shines. 🌟 | encode | 2024-01-13 | 2018-06-25 | 292 | 30.991687 | https://avatars.githubusercontent.com/u/19159390?v=4 | The little ASGI framework that shines. 🌟 | ['async', 'http', 'websockets'] | ['async', 'http', 'websockets'] | 2024-01-13 | [('pallets/quart', 0.7032433152198792, 'web', 0), ('neoteroi/blacksheep', 0.6760811805725098, 'web', 1), ('encode/uvicorn', 0.6668508052825928, 'web', 1), ('aio-libs/aiohttp', 0.6300008296966553, 'web', 2), ('miguelgrinberg/python-socketio', 0.6212427616119385, 'util', 0), ('encode/httpx', 0.5981119275093079, 'web', 1), ('tiangolo/asyncer', 0.5958313345909119, 'perf', 1), ('alirn76/panther', 0.5935547351837158, 'web', 0), ('huge-success/sanic', 0.5865360498428345, 'web', 0), ('tornadoweb/tornado', 0.57993084192276, 'web', 0), ('agronholm/anyio', 0.5785104036331177, 'perf', 0), ('mlc-ai/web-llm', 0.5606010556221008, 'llm', 0), ('starlite-api/starlite', 0.5545772314071655, 'web', 0), ('emmett-framework/emmett', 0.5443409085273743, 'web', 0), ('airtai/faststream', 0.5320852398872375, 'perf', 0), ('python-trio/trio', 0.5227438807487488, 'perf', 1), ('klen/muffin', 0.5224829912185669, 'web', 0), ('jordaneremieff/mangum', 0.5116714239120483, 'web', 0), ('magicstack/uvloop', 0.5062094926834106, 'util', 1), ('pallets/werkzeug', 0.5027870535850525, 'web', 1)] | 255 | 6 | null | 3.44 | 125 | 106 | 68 | 0 | 17 | 25 | 17 | 125 | 210 | 90 | 1.7 | 64 |
1,120 | math | https://github.com/cupy/cupy | [] | null | [] | [] | null | null | null | cupy/cupy | cupy | 7,446 | 735 | 126 | Python | https://cupy.dev | NumPy & SciPy for GPU | cupy | 2024-01-13 | 2016-11-01 | 378 | 19.698413 | https://avatars.githubusercontent.com/u/23187665?v=4 | NumPy & SciPy for GPU | ['cublas', 'cuda', 'cudnn', 'cupy', 'curand', 'cusolver', 'cusparse', 'cusparselt', 'cutensor', 'gpu', 'nccl', 'numpy', 'nvrtc', 'nvtx', 'rocm', 'scipy', 'tensor'] | ['cublas', 'cuda', 'cudnn', 'cupy', 'curand', 'cusolver', 'cusparse', 'cusparselt', 'cutensor', 'gpu', 'nccl', 'numpy', 'nvrtc', 'nvtx', 'rocm', 'scipy', 'tensor'] | 2024-01-12 | [('rapidsai/cudf', 0.6393476724624634, 'pandas', 2), ('numpy/numpy', 0.6240665912628174, 'math', 1), ('nvidia/cuda-python', 0.5955917835235596, 'ml', 0), ('pytorch/pytorch', 0.5749741196632385, 'ml-dl', 3), ('nvidia/tensorrt-llm', 0.5631754994392395, 'viz', 1), ('numba/numba', 0.555233895778656, 'perf', 2), ('cvxgrp/pymde', 0.5531930327415466, 'ml', 2), ('arogozhnikov/einops', 0.5499424934387207, 'ml-dl', 3), ('roban/cosmolopy', 0.5431826710700989, 'sim', 0), ('huggingface/accelerate', 0.5428050756454468, 'ml', 0), ('scipy/scipy', 0.5399492979049683, 'math', 1), ('pytorch/torchrec', 0.5291244387626648, 'ml-dl', 2), ('blackhc/toma', 0.5264122486114502, 'ml-dl', 1), ('google/tf-quant-finance', 0.5244703888893127, 'finance', 1), ('nvidia/warp', 0.518425464630127, 'sim', 1), ('marcomusy/vedo', 0.5182294845581055, 'viz', 1), ('rentruewang/koila', 0.5168486833572388, 'ml', 0), ('luispedro/mahotas', 0.5168439745903015, 'viz', 1), ('google/jax', 0.5167858004570007, 'ml', 1), ('tensorly/tensorly', 0.5093604922294617, 'ml-dl', 3), ('hips/autograd', 0.5063801407814026, 'ml', 0), ('xl0/lovely-numpy', 0.5024915933609009, 'util', 1), ('isl-org/open3d', 0.5012453198432922, 'sim', 2), ('pyo3/rust-numpy', 0.5001054406166077, 'util', 1)] | 354 | 4 | null | 31.12 | 236 | 156 | 88 | 0 | 12 | 19 | 12 | 236 | 544 | 90 | 2.3 | 64 |
351 | ml-ops | https://github.com/activeloopai/deeplake | ['vector-search'] | null | [] | [] | null | null | null | activeloopai/deeplake | deeplake | 7,381 | 570 | 84 | Python | https://activeloop.ai | Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai | activeloopai | 2024-01-13 | 2019-08-09 | 233 | 31.600612 | https://avatars.githubusercontent.com/u/34816118?v=4 | Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai | ['ai', 'computer-vision', 'cv', 'data-science', 'data-version-control', 'datalake', 'datasets', 'deep-learning', 'image-processing', 'langchain', 'large-language-models', 'llm', 'machine-learning', 'ml', 'mlops', 'pytorch', 'tensorflow', 'vector-database', 'vector-search'] | ['ai', 'computer-vision', 'cv', 'data-science', 'data-version-control', 'datalake', 'datasets', 'deep-learning', 'image-processing', 'langchain', 'large-language-models', 'llm', 'machine-learning', 'ml', 'mlops', 'pytorch', 'tensorflow', 'vector-database', 'vector-search'] | 2024-01-13 | [('lancedb/lancedb', 0.7212356925010681, 'data', 1), ('superduperdb/superduperdb', 0.7059310674667358, 'data', 5), ('qdrant/qdrant', 0.6835601329803467, 'data', 4), ('jina-ai/vectordb', 0.639483630657196, 'data', 2), ('mindsdb/mindsdb', 0.630451500415802, 'data', 4), ('milvus-io/bootcamp', 0.6203997731208801, 'data', 2), ('dgarnitz/vectorflow', 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776 | diffusion | https://github.com/carson-katri/dream-textures | [] | null | [] | [] | null | null | null | carson-katri/dream-textures | dream-textures | 7,370 | 394 | 108 | Python | null | Stable Diffusion built-in to Blender | carson-katri | 2024-01-14 | 2022-09-08 | 72 | 101.355599 | null | Stable Diffusion built-in to Blender | ['ai', 'blender', 'blender-addon', 'image-generation', 'stable-diffusion'] | ['ai', 'blender', 'blender-addon', 'image-generation', 'stable-diffusion'] | 2023-11-07 | [('automatic1111/stable-diffusion-webui', 0.7420854568481445, 'diffusion', 3), ('stability-ai/stability-sdk', 0.7153577208518982, 'diffusion', 1), ('bentoml/onediffusion', 0.6899959444999695, 'diffusion', 2), ('comfyanonymous/comfyui', 0.6763654947280884, 'diffusion', 1), ('albarji/mixture-of-diffusers', 0.6328878998756409, 'diffusion', 2), ('invoke-ai/invokeai', 0.6296207904815674, 'diffusion', 2), ('nateraw/stable-diffusion-videos', 0.6127192378044128, 'diffusion', 1), ('divamgupta/stable-diffusion-tensorflow', 0.6051181554794312, 'diffusion', 0), ('xavierxiao/dreambooth-stable-diffusion', 0.5931910872459412, 'diffusion', 1), ('mlc-ai/web-stable-diffusion', 0.5855890512466431, 'diffusion', 1), ('thereforegames/unprompted', 0.5799620747566223, 'diffusion', 1), ('jina-ai/discoart', 0.5772116184234619, 'diffusion', 1), ('huggingface/diffusers', 0.5772011280059814, 'diffusion', 2), ('ashawkey/stable-dreamfusion', 0.5740616917610168, 'diffusion', 1), ('timothybrooks/instruct-pix2pix', 0.5679231286048889, 'diffusion', 0), ('lunarring/latentblending', 0.5618883967399597, 'diffusion', 1), ('lkwq007/stablediffusion-infinity', 0.5580441951751709, 'diffusion', 1), ('civitai/sd_civitai_extension', 0.5569747686386108, 'llm', 0), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5474333763122559, 'web', 0), ('lllyasviel/controlnet', 0.5427067279815674, 'diffusion', 0), ('sanster/lama-cleaner', 0.5392587780952454, 'ml-dl', 1), ('divamgupta/diffusionbee-stable-diffusion-ui', 0.534104585647583, 'diffusion', 1), ('open-mmlab/mmediting', 0.5198704600334167, 'ml', 1), ('saharmor/dalle-playground', 0.5181798934936523, 'diffusion', 1), ('apple/ml-stable-diffusion', 0.5164445042610168, 'diffusion', 0), ('tanelp/tiny-diffusion', 0.5146340727806091, 'diffusion', 0)] | 11 | 5 | null | 0.54 | 65 | 31 | 16 | 0 | 4 | 10 | 4 | 65 | 113 | 90 | 1.7 | 64 |
1,881 | pandas | https://github.com/rapidsai/cudf | ['pandas', 'gpu', 'dataframe'] | cuDF is a GPU DataFrame library for loading joining, aggregating, filtering, and otherwise manipulating data | [] | [] | null | null | null | rapidsai/cudf | cudf | 6,898 | 797 | 146 | C++ | https://docs.rapids.ai/api/cudf/stable/ | cuDF - GPU DataFrame Library | rapidsai | 2024-01-13 | 2017-05-07 | 351 | 19.636438 | https://avatars.githubusercontent.com/u/43887749?v=4 | cuDF - GPU DataFrame Library | ['arrow', 'cpp', 'cuda', 'cudf', 'dask', 'data-analysis', 'data-science', 'dataframe', 'gpu', 'pandas', 'pydata', 'rapids'] | ['arrow', 'cpp', 'cuda', 'cudf', 'dask', 'data-analysis', 'data-science', 'dataframe', 'gpu', 'pandas', 'pydata', 'rapids'] | 2024-01-12 | [('cupy/cupy', 0.6393476724624634, 'math', 2), ('hi-primus/optimus', 0.6309337019920349, 'ml-ops', 4), ('pandas-dev/pandas', 0.6205441355705261, 'pandas', 5), ('man-group/dtale', 0.5755491256713867, 'viz', 3), ('jmcarpenter2/swifter', 0.5688180923461914, 'pandas', 2), ('vaexio/vaex', 0.56623375415802, 'perf', 2), ('mito-ds/monorepo', 0.5557620525360107, 'jupyter', 3), ('apache/arrow', 0.5487073659896851, 'data', 3), ('pola-rs/polars', 0.5434831380844116, 'pandas', 2), ('twopirllc/pandas-ta', 0.542910099029541, 'finance', 2), ('eventual-inc/daft', 0.5403209924697876, 'pandas', 2), ('nvidia/cuda-python', 0.5373781323432922, 'ml', 0), ('ydataai/ydata-profiling', 0.5349627733230591, 'pandas', 3), ('polyaxon/datatile', 0.5338151454925537, 'pandas', 3), ('lux-org/lux', 0.5294429063796997, 'viz', 2), ('kanaries/pygwalker', 0.5281388759613037, 'pandas', 3), ('google/tf-quant-finance', 0.5263254046440125, 'finance', 1), ('graphistry/pygraphistry', 0.5241773724555969, 'data', 4), ('holoviz/spatialpandas', 0.5126527547836304, 'pandas', 1), ('nalepae/pandarallel', 0.5124971866607666, 'pandas', 1), ('holoviz/hvplot', 0.5121793746948242, 'pandas', 0), ('mementum/bta-lib', 0.5101376175880432, 'finance', 0), ('mwaskom/seaborn', 0.5099605917930603, 'viz', 2), ('adamerose/pandasgui', 0.5097667574882507, 'pandas', 2), ('has2k1/plotnine', 0.5067694783210754, 'viz', 1), ('tkrabel/bamboolib', 0.5010843276977539, 'pandas', 1), ('dylanhogg/awesome-python', 0.5004510283470154, 'study', 2), ('pytorch/torchrec', 0.5002225637435913, 'ml-dl', 2)] | 269 | 3 | null | 33.96 | 609 | 405 | 81 | 0 | 12 | 15 | 12 | 606 | 1,425 | 90 | 2.4 | 64 |
1,285 | llm | https://github.com/zilliztech/gptcache | [] | null | [] | [] | null | null | null | zilliztech/gptcache | GPTCache | 5,883 | 417 | 56 | Python | https://gptcache.readthedocs.io | Semantic cache for LLMs. Fully integrated with LangChain and llama_index. | zilliztech | 2024-01-14 | 2023-03-24 | 44 | 131.990385 | https://avatars.githubusercontent.com/u/18416694?v=4 | Semantic cache for LLMs. Fully integrated with LangChain and llama_index. | ['aigc', 'autogpt', 'babyagi', 'chatbot', 'chatgpt', 'chatgpt-api', 'dolly', 'gpt', 'langchain', 'llama', 'llama-index', 'llm', 'memcache', 'milvus', 'openai', 'redis', 'semantic-search', 'similarity-search', 'vector-search'] | ['aigc', 'autogpt', 'babyagi', 'chatbot', 'chatgpt', 'chatgpt-api', 'dolly', 'gpt', 'langchain', 'llama', 'llama-index', 'llm', 'memcache', 'milvus', 'openai', 'redis', 'semantic-search', 'similarity-search', 'vector-search'] | 2023-11-28 | [('shishirpatil/gorilla', 0.6505623459815979, 'llm', 2), ('intel/intel-extension-for-transformers', 0.6376039981842041, 'perf', 1), ('deepset-ai/haystack', 0.6036768555641174, 'llm', 2), ('jerryjliu/llama_index', 0.5998677611351013, 'llm', 3), ('run-llama/rags', 0.5993092060089111, 'llm', 4), ('run-llama/llama-hub', 0.5969860553741455, 'data', 1), ('bobazooba/xllm', 0.5947780013084412, 'llm', 5), ('dylanhogg/llmgraph', 0.5875337719917297, 'ml', 2), ('pathwaycom/llm-app', 0.5837850570678711, 'llm', 2), ('hwchase17/langchain', 0.5693703293800354, 'llm', 2), ('nomic-ai/gpt4all', 0.5606859922409058, 'llm', 1), ('langchain-ai/langgraph', 0.5597312450408936, 'llm', 1), ('bigscience-workshop/petals', 0.5577248334884644, 'data', 3), ('microsoft/autogen', 0.5542406439781189, 'llm', 3), ('paddlepaddle/paddlenlp', 0.5492423176765442, 'llm', 2), ('neuml/txtai', 0.5468195080757141, 'nlp', 3), ('h2oai/h2o-llmstudio', 0.5407289266586304, 'llm', 5), ('dgilland/cacheout', 0.540678858757019, 'perf', 0), ('vllm-project/vllm', 0.540032148361206, 'llm', 3), ('berriai/litellm', 0.539711594581604, 'llm', 3), ('hiyouga/llama-factory', 0.5300214290618896, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.5300213694572449, 'llm', 3), ('li-plus/chatglm.cpp', 0.5297065377235413, 'llm', 0), ('lancedb/lancedb', 0.5283774137496948, 'data', 2), ('alphasecio/langchain-examples', 0.5278271436691284, 'llm', 3), ('deep-diver/llm-as-chatbot', 0.5247036218643188, 'llm', 1), ('tigerlab-ai/tiger', 0.5229496955871582, 'llm', 1), ('explosion/spacy-llm', 0.5211718082427979, 'llm', 4), ('salesforce/xgen', 0.5199717283248901, 'llm', 1), ('python-cachier/cachier', 0.5158444046974182, 'perf', 0), ('embedchain/embedchain', 0.5112298727035522, 'llm', 2), ('confident-ai/deepeval', 0.5101267099380493, 'testing', 2), ('continuum-llms/chatgpt-memory', 0.5097682476043701, 'llm', 3), ('nomic-ai/semantic-search-app-template', 0.5088302493095398, 'study', 2), ('thudm/chatglm2-6b', 0.507978081703186, 'llm', 1), ('long2ice/fastapi-cache', 0.506112813949585, 'web', 1), ('mooler0410/llmspracticalguide', 0.5039639472961426, 'study', 0), ('bentoml/openllm', 0.5029482245445251, 'ml-ops', 2), ('young-geng/easylm', 0.5008785724639893, 'llm', 2)] | 41 | 1 | null | 9.54 | 45 | 16 | 10 | 2 | 40 | 49 | 40 | 45 | 68 | 90 | 1.5 | 64 |
1,834 | llm | https://github.com/run-llama/rags | ['rag'] | null | [] | [] | null | null | null | run-llama/rags | rags | 5,280 | 640 | 46 | Python | null | Build ChatGPT over your data, all with natural language | run-llama | 2024-01-14 | 2023-11-16 | 10 | 492.8 | https://avatars.githubusercontent.com/u/130722866?v=4 | Build ChatGPT over your data, all with natural language | ['agent', 'chatbot', 'chatgpt', 'gpts', 'llamaindex', 'llm', 'openai', 'rag', 'streamlit'] | ['agent', 'chatbot', 'chatgpt', 'gpts', 'llamaindex', 'llm', 'openai', 'rag', 'streamlit'] | 2023-12-05 | [('embedchain/embedchain', 0.775257408618927, 'llm', 2), ('xtekky/gpt4free', 0.7228777408599854, 'llm', 3), ('microsoft/autogen', 0.713228166103363, 'llm', 2), ('openai/openai-cookbook', 0.7131730318069458, 'ml', 2), ('killianlucas/open-interpreter', 0.6841922998428345, 'llm', 1), ('nomic-ai/gpt4all', 0.679734468460083, 'llm', 1), ('blinkdl/chatrwkv', 0.678069531917572, 'llm', 2), ('minimaxir/simpleaichat', 0.6775078177452087, 'llm', 1), ('togethercomputer/openchatkit', 0.6478996872901917, 'nlp', 1), ('mmabrouk/chatgpt-wrapper', 0.644103467464447, 'llm', 4), ('shishirpatil/gorilla', 0.6374510526657104, 'llm', 2), ('lm-sys/fastchat', 0.6331033110618591, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6312287449836731, 'perf', 1), ('deepset-ai/haystack', 0.6311088800430298, 'llm', 1), ('gventuri/pandas-ai', 0.6272019743919373, 'pandas', 1), ('mayooear/gpt4-pdf-chatbot-langchain', 0.6243221163749695, 'llm', 1), ('rasahq/rasa', 0.6235318779945374, 'llm', 1), ('prefecthq/marvin', 0.6145691275596619, 'nlp', 2), ('chainlit/chainlit', 0.61057049036026, 'llm', 3), ('rcgai/simplyretrieve', 0.6102337837219238, 'llm', 0), ('chatarena/chatarena', 0.6069520711898804, 'llm', 1), ('fasteval/fasteval', 0.6045003533363342, 'llm', 1), ('openlmlab/moss', 0.6012157797813416, 'llm', 1), ('hwchase17/langchain', 0.6003484129905701, 'llm', 1), ('dylanhogg/llmgraph', 0.5997524857521057, 'ml', 2), ('zilliztech/gptcache', 0.5993092060089111, 'llm', 4), ('larsbaunwall/bricky', 0.5981244444847107, 'llm', 1), ('mlc-ai/web-llm', 0.5972565412521362, 'llm', 2), ('pathwaycom/llm-app', 0.5891484618186951, 'llm', 3), ('databrickslabs/dolly', 0.5840879678726196, 'llm', 1), ('mindsdb/mindsdb', 0.5839447975158691, 'data', 2), ('openai/tiktoken', 0.5739045143127441, 'nlp', 1), ('cheshire-cat-ai/core', 0.5686349868774414, 'llm', 2), ('microsoft/generative-ai-for-beginners', 0.5668851137161255, 'study', 2), ('microsoft/promptflow', 0.5604910254478455, 'llm', 2), ('deep-diver/llm-as-chatbot', 0.5595909953117371, 'llm', 1), ('lupantech/chameleon-llm', 0.5582309365272522, 'llm', 3), ('continuum-llms/chatgpt-memory', 0.5546180605888367, 'llm', 1), ('next-gpt/next-gpt', 0.5521267652511597, 'llm', 2), ('mnotgod96/appagent', 0.5510104894638062, 'llm', 3), ('promptslab/promptify', 0.5508096814155579, 'nlp', 2), ('alphasecio/langchain-examples', 0.5506168007850647, 'llm', 3), ('thudm/chatglm2-6b', 0.547817587852478, 'llm', 1), ('gunthercox/chatterbot-corpus', 0.5412566065788269, 'nlp', 0), ('farizrahman4u/loopgpt', 0.5412454605102539, 'llm', 1), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5412412881851196, 'llm', 0), ('laion-ai/open-assistant', 0.5403715968132019, 'llm', 1), ('h2oai/h2ogpt', 0.5400290489196777, 'llm', 2), ('deeppavlov/deeppavlov', 0.5382777452468872, 'nlp', 1), ('openai/chatgpt-retrieval-plugin', 0.5382370948791504, 'llm', 1), ('li-plus/chatglm.cpp', 0.5372152328491211, 'llm', 0), ('bobazooba/xllm', 0.5356626510620117, 'llm', 3), ('langchain-ai/opengpts', 0.5282418131828308, 'llm', 0), ('lianjiatech/belle', 0.5264316201210022, 'llm', 0), ('argilla-io/argilla', 0.5243651866912842, 'nlp', 1), ('microsoft/promptcraft-robotics', 0.5236408710479736, 'sim', 2), ('krohling/bondai', 0.5235958099365234, 'llm', 0), ('bhaskatripathi/pdfgpt', 0.5228466987609863, 'llm', 0), ('aiwaves-cn/agents', 0.5222904682159424, 'nlp', 1), ('minimaxir/gpt-2-simple', 0.5192126035690308, 'llm', 1), ('bigscience-workshop/petals', 0.5189594626426697, 'data', 1), ('explosion/spacy-llm', 0.5166354775428772, 'llm', 2), ('langchain-ai/langgraph', 0.5150389671325684, 'llm', 0), ('guidance-ai/guidance', 0.5145743489265442, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5137847065925598, 'llm', 3), ('langchain-ai/chat-langchain', 0.5135616064071655, 'llm', 1), ('openai/gpt-discord-bot', 0.5125691890716553, 'llm', 0), ('whu-zqh/chatgpt-vs.-bert', 0.5091956257820129, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5037953853607178, 'llm', 1), ('hiyouga/llama-factory', 0.5037953853607178, 'llm', 1), ('explosion/spacy-streamlit', 0.5017317533493042, 'nlp', 1), ('young-geng/easylm', 0.5016451478004456, 'llm', 1)] | 5 | 2 | null | 0.33 | 58 | 31 | 2 | 1 | 0 | 0 | 0 | 58 | 68 | 90 | 1.2 | 64 |
1,592 | llm | https://github.com/skypilot-org/skypilot | ['ml-platform', 'ml-infrastructure'] | null | [] | [] | null | null | null | skypilot-org/skypilot | skypilot | 4,870 | 313 | 61 | Python | https://skypilot.readthedocs.io | SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface. | skypilot-org | 2024-01-13 | 2021-08-11 | 128 | 37.793792 | https://avatars.githubusercontent.com/u/109387420?v=4 | SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface. | ['cloud-computing', 'cloud-management', 'cost-management', 'cost-optimization', 'data-science', 'deep-learning', 'distributed-training', 'finops', 'gpu', 'hyperparameter-tuning', 'job-queue', 'job-scheduler', 'llm-serving', 'llm-training', 'machine-learning', 'ml-infrastructure', 'ml-platform', 'multicloud', 'spot-instances', 'tpu'] | ['cloud-computing', 'cloud-management', 'cost-management', 'cost-optimization', 'data-science', 'deep-learning', 'distributed-training', 'finops', 'gpu', 'hyperparameter-tuning', 'job-queue', 'job-scheduler', 'llm-serving', 'llm-training', 'machine-learning', 'ml-infrastructure', 'ml-platform', 'multicloud', 'spot-instances', 'tpu'] | 2024-01-14 | [('polyaxon/polyaxon', 0.6188631057739258, 'ml-ops', 3), ('lithops-cloud/lithops', 0.6185680031776428, 'ml-ops', 2), ('googlecloudplatform/vertex-ai-samples', 0.6106062531471252, 'ml', 1), ('netflix/metaflow', 0.6102747321128845, 'ml-ops', 4), ('jina-ai/jina', 0.5877841711044312, 'ml', 2), ('bigscience-workshop/petals', 0.5853170156478882, 'data', 2), ('flyteorg/flyte', 0.5598949790000916, 'ml-ops', 2), ('pathwaycom/llm-app', 0.554336428642273, 'llm', 1), ('zenml-io/mlstacks', 0.5491843819618225, 'ml-ops', 0), ('bentoml/bentoml', 0.5428783297538757, 'ml-ops', 3), ('bentoml/openllm', 0.536402702331543, 'ml-ops', 1), ('bodywork-ml/bodywork-core', 0.5361641049385071, 'ml-ops', 2), ('localstack/localstack', 0.5336942672729492, 'util', 0), ('alpa-projects/alpa', 0.5307222008705139, 'ml-dl', 3), ('determined-ai/determined', 0.5281897783279419, 'ml-ops', 7), ('orchest/orchest', 0.5275050401687622, 'ml-ops', 2), ('microsoft/semantic-kernel', 0.5244306325912476, 'llm', 0), ('fugue-project/fugue', 0.5239272117614746, 'pandas', 1), ('vllm-project/vllm', 0.5184321403503418, 'llm', 1), ('mlflow/mlflow', 0.514528214931488, 'ml-ops', 1), ('predibase/lorax', 0.5144446492195129, 'llm', 2), ('hpcaitech/colossalai', 0.5133247971534729, 'llm', 1), ('cheshire-cat-ai/core', 0.510378360748291, 'llm', 0), ('shishirpatil/gorilla', 0.5099743008613586, 'llm', 0), ('superduperdb/superduperdb', 0.5078701376914978, 'data', 1), ('backtick-se/cowait', 0.5072562098503113, 'util', 1), ('pytorchlightning/pytorch-lightning', 0.5027073621749878, 'ml-dl', 3), ('microsoft/promptflow', 0.5022432208061218, 'llm', 0), ('uber/fiber', 0.5006906390190125, 'data', 1)] | 61 | 5 | null | 11.79 | 532 | 288 | 30 | 0 | 9 | 6 | 9 | 533 | 790 | 90 | 1.5 | 64 |
1,525 | llm | https://github.com/stanfordnlp/dspy | ['reasoning', 'prompting', 'fine-tuning', 'retrieval'] | null | [] | [] | 1 | null | null | stanfordnlp/dspy | dspy | 4,712 | 290 | 90 | Python | null | Stanford DSPy: The framework for programming—not prompting—foundation models | stanfordnlp | 2024-01-14 | 2023-01-09 | 55 | 85.450777 | https://avatars.githubusercontent.com/u/3046006?v=4 | Stanford DSPy: The framework for programming—not prompting—foundation models | [] | ['fine-tuning', 'prompting', 'reasoning', 'retrieval'] | 2024-01-13 | [('srush/minichain', 0.6080040335655212, 'llm', 0), ('python/cpython', 0.5970360040664673, 'util', 0), ('kyegomez/tree-of-thoughts', 0.5961645245552063, 'llm', 0), ('reasoning-machines/pal', 0.5881893038749695, 'llm', 1), ('eleutherai/pyfra', 0.5839141607284546, 'ml', 0), ('keirp/automatic_prompt_engineer', 0.5835668444633484, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5695632696151733, 'llm', 0), ('pytoolz/toolz', 0.5550901889801025, 'util', 0), ('google/pyglove', 0.5547299385070801, 'util', 0), ('bigscience-workshop/promptsource', 0.5486031770706177, 'nlp', 0), ('guidance-ai/guidance', 0.5456482768058777, 'llm', 0), ('hazyresearch/ama_prompting', 0.540431022644043, 'llm', 0), ('hazyresearch/manifest', 0.5367062091827393, 'llm', 0), ('evhub/coconut', 0.5305084586143494, 'util', 0), ('juncongmoo/pyllama', 0.5301841497421265, 'llm', 0), ('llmware-ai/llmware', 0.5297998785972595, 'llm', 0), ('pyston/pyston', 0.5251495838165283, 'util', 0), ('pexpect/pexpect', 0.5249006152153015, 'util', 0), ('promptslab/promptify', 0.5224989056587219, 'nlp', 1), ('lupantech/chameleon-llm', 0.5166156888008118, 'llm', 1), ('eth-sri/lmql', 0.516359806060791, 'llm', 0), ('databrickslabs/dolly', 0.5139095783233643, 'llm', 0), ('modularml/mojo', 0.5088305473327637, 'util', 0), ('facebookresearch/reagent', 0.5081221461296082, 'ml-rl', 0), ('norvig/pytudes', 0.5077176690101624, 'util', 0), ('microsoft/pycodegpt', 0.5060772895812988, 'llm', 0), ('optimalscale/lmflow', 0.5005626082420349, 'llm', 0), ('dylanhogg/awesome-python', 0.5004346966743469, 'study', 0)] | 44 | 4 | null | 8.67 | 140 | 90 | 12 | 0 | 0 | 0 | 0 | 138 | 302 | 90 | 2.2 | 64 |
1,890 | llm | https://github.com/mnotgod96/appagent | [] | null | [] | [] | null | null | null | mnotgod96/appagent | AppAgent | 3,223 | 312 | 40 | Python | https://appagent-official.github.io/ | AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps. | mnotgod96 | 2024-01-14 | 2023-12-20 | 5 | 550.268293 | null | AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps. | ['agent', 'chatgpt', 'generative-ai', 'gpt4', 'gpt4v', 'llm'] | ['agent', 'chatgpt', 'generative-ai', 'gpt4', 'gpt4v', 'llm'] | 2024-01-03 | [('pathwaycom/llm-app', 0.6296766400337219, 'llm', 1), ('microsoft/semantic-kernel', 0.6219491362571716, 'llm', 1), ('microsoft/promptflow', 0.5954347252845764, 'llm', 2), ('microsoft/autogen', 0.5801144242286682, 'llm', 1), ('geekan/metagpt', 0.5650525093078613, 'llm', 2), ('embedchain/embedchain', 0.5549655556678772, 'llm', 2), ('next-gpt/next-gpt', 0.5528967976570129, 'llm', 2), ('run-llama/rags', 0.5510104894638062, 'llm', 3), ('nomic-ai/gpt4all', 0.5476191639900208, 'llm', 0), ('chatarena/chatarena', 0.5439862012863159, 'llm', 1), ('deepset-ai/haystack', 0.5397396087646484, 'llm', 2), ('deep-diver/llm-as-chatbot', 0.5356595516204834, 'llm', 0), ('prefecthq/marvin', 0.5343064665794373, 'nlp', 1), ('luodian/otter', 0.5246831774711609, 'llm', 1), ('farizrahman4u/loopgpt', 0.5192574858665466, 'llm', 2), ('h2oai/h2o-llmstudio', 0.5174366235733032, 'llm', 3), ('haotian-liu/llava', 0.5170363187789917, 'llm', 1), ('operand/agency', 0.51549232006073, 'llm', 2), ('mmabrouk/chatgpt-wrapper', 0.5122302174568176, 'llm', 3), ('microsoft/promptcraft-robotics', 0.5117555260658264, 'sim', 2), ('humanoidagents/humanoidagents', 0.5099534392356873, 'sim', 1), ('mlc-ai/mlc-llm', 0.5084356665611267, 'llm', 1), ('hwchase17/langchain', 0.5082905888557434, 'llm', 0), ('xtekky/gpt4free', 0.5081965923309326, 'llm', 2), ('intel/intel-extension-for-transformers', 0.5081307888031006, 'perf', 0), ('langchain-ai/langgraph', 0.5023365020751953, 'llm', 0), ('minimaxir/simpleaichat', 0.501400351524353, 'llm', 1)] | 6 | 3 | null | 0.42 | 32 | 5 | 1 | 0 | 0 | 0 | 0 | 32 | 41 | 90 | 1.3 | 64 |
1,101 | llm | https://github.com/tatsu-lab/stanford_alpaca | [] | null | [] | [] | null | null | null | tatsu-lab/stanford_alpaca | stanford_alpaca | 28,052 | 3,980 | 335 | Python | https://crfm.stanford.edu/2023/03/13/alpaca.html | Code and documentation to train Stanford's Alpaca models, and generate the data. | tatsu-lab | 2024-01-13 | 2023-03-10 | 46 | 602.343558 | https://avatars.githubusercontent.com/u/61893194?v=4 | Code and documentation to train Stanford's Alpaca models, and generate the data. | ['deep-learning', 'instruction-following', 'language-model'] | ['deep-learning', 'instruction-following', 'language-model'] | 2023-05-30 | [('optimalscale/lmflow', 0.6111303567886353, 'llm', 3), ('hannibal046/awesome-llm', 0.6053584218025208, 'study', 1), ('yizhongw/self-instruct', 0.5977901816368103, 'llm', 1), ('jonasgeiping/cramming', 0.5919219851493835, 'nlp', 1), ('huggingface/text-generation-inference', 0.5844063758850098, 'llm', 1), ('juncongmoo/pyllama', 0.5793993473052979, 'llm', 0), ('togethercomputer/redpajama-data', 0.5778451561927795, 'llm', 0), ('tiger-ai-lab/mammoth', 0.5743323564529419, 'llm', 0), ('paperswithcode/galai', 0.5739641785621643, 'llm', 1), ('stanfordnlp/dspy', 0.5695632696151733, 'llm', 0), ('infinitylogesh/mutate', 0.5620525479316711, 'nlp', 1), ('freedomintelligence/llmzoo', 0.5588739514350891, 'llm', 1), ('openai/gpt-2', 0.5557239055633545, 'llm', 0), ('graykode/nlp-tutorial', 0.5533468723297119, 'study', 0), ('nvidia/deeplearningexamples', 0.5533385872840881, 'ml-dl', 1), ('yueyu1030/attrprompt', 0.5511519312858582, 'llm', 0), ('eleutherai/the-pile', 0.5507524013519287, 'data', 0), ('cgpotts/cs224u', 0.5506641268730164, 'study', 0), ('lianjiatech/belle', 0.5461639761924744, 'llm', 0), ('facebookresearch/shepherd', 0.5445735454559326, 'llm', 1), ('huawei-noah/pretrained-language-model', 0.5441707372665405, 'nlp', 0), ('mooler0410/llmspracticalguide', 0.5418017506599426, 'study', 0), ('lm-sys/fastchat', 0.5374524593353271, 'llm', 1), ('young-geng/easylm', 0.536756694316864, 'llm', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5365834832191467, 'study', 0), ('cg123/mergekit', 0.5332975387573242, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5329034924507141, 'llm', 1), ('rafiqhasan/auto-tensorflow', 0.5314496755599976, 'ml-dl', 0), ('ofa-sys/ofa', 0.5313153266906738, 'llm', 0), ('llmware-ai/llmware', 0.5306206345558167, 'llm', 0), ('reasoning-machines/pal', 0.5286970734596252, 'llm', 1), ('openai/finetune-transformer-lm', 0.5281931757926941, 'llm', 0), ('keras-team/keras-nlp', 0.5273944735527039, 'nlp', 1), ('openbmb/toolbench', 0.5260429382324219, 'llm', 0), ('srush/minichain', 0.5253647565841675, 'llm', 0), ('salesforce/xgen', 0.52476966381073, 'llm', 1), ('huggingface/transformers', 0.5228704214096069, 'nlp', 2), ('d2l-ai/d2l-en', 0.5226318836212158, 'study', 1), ('tensorflow/tensor2tensor', 0.5224913954734802, 'ml', 1), ('ai21labs/lm-evaluation', 0.5184262990951538, 'llm', 1), ('deepset-ai/farm', 0.5168743133544922, 'nlp', 1), ('paddlepaddle/paddlenlp', 0.5149617195129395, 'llm', 0), ('conceptofmind/toolformer', 0.5121525526046753, 'llm', 1), ('microsoft/unilm', 0.511536180973053, 'nlp', 0), ('keirp/automatic_prompt_engineer', 0.511340320110321, 'llm', 1), ('databrickslabs/dolly', 0.5099220275878906, 'llm', 0), ('lucidrains/toolformer-pytorch', 0.5094295740127563, 'llm', 2), ('rasbt/stat453-deep-learning-ss20', 0.5087552666664124, 'study', 0), ('titanml/takeoff', 0.507792055606842, 'llm', 1), ('neulab/prompt2model', 0.5068913102149963, 'llm', 1), ('ageron/handson-ml2', 0.5068382620811462, 'ml', 0), ('rasbt/deeplearning-models', 0.5054455399513245, 'ml-dl', 0), ('microsoft/generative-ai-for-beginners', 0.5033739805221558, 'study', 1), ('explosion/spacy-models', 0.5031586289405823, 'nlp', 0), ('declare-lab/instruct-eval', 0.5018754005432129, 'llm', 0)] | 5 | 3 | null | 0.6 | 19 | 4 | 10 | 8 | 0 | 0 | 0 | 19 | 20 | 90 | 1.1 | 63 |
62 | viz | https://github.com/plotly/dash | [] | null | [] | [] | null | null | null | plotly/dash | dash | 19,929 | 2,030 | 413 | Python | https://plotly.com/dash | Data Apps & Dashboards for Python. No JavaScript Required. | plotly | 2024-01-14 | 2015-04-10 | 459 | 43.364315 | https://avatars.githubusercontent.com/u/5997976?v=4 | Data Apps & Dashboards for Python. 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1,699 | util | https://github.com/mkdocs/mkdocs | [] | null | [] | [] | null | null | null | mkdocs/mkdocs | mkdocs | 17,718 | 2,353 | 231 | Python | https://www.mkdocs.org | Project documentation with Markdown. | mkdocs | 2024-01-14 | 2014-01-11 | 524 | 33.785345 | https://avatars.githubusercontent.com/u/9692741?v=4 | Project documentation with Markdown. | ['documentation', 'markdown', 'mkdocs', 'static-site-generator'] | ['documentation', 'markdown', 'mkdocs', 'static-site-generator'] | 2023-12-23 | [('mkdocstrings/mkdocstrings', 0.6345070600509644, 'util', 1), ('squidfunk/mkdocs-material', 0.6341920495033264, 'util', 2), ('sphinx-doc/sphinx', 0.6297897100448608, 'util', 2), ('getpelican/pelican', 0.5778642296791077, 'web', 1), ('mitmproxy/pdoc', 0.5321336984634399, 'util', 1), ('pdoc3/pdoc', 0.5143741369247437, 'util', 1)] | 246 | 5 | null | 3.58 | 122 | 94 | 122 | 1 | 5 | 6 | 5 | 122 | 224 | 90 | 1.8 | 63 |
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63 | viz | https://github.com/plotly/plotly.py | [] | null | [] | [] | null | null | null | plotly/plotly.py | plotly.py | 14,686 | 2,467 | 280 | Python | https://plotly.com/python/ | The interactive graphing library for Python :sparkles: This project now includes Plotly Express! | plotly | 2024-01-14 | 2013-11-21 | 531 | 27.620097 | https://avatars.githubusercontent.com/u/5997976?v=4 | The interactive graphing library for Python ✨ This project now includes Plotly Express! | ['d3', 'dashboard', 'declarative', 'graph-library', 'interactive', 'jupyter-notebook', 'plotly', 'plotly-dash', 'plotlyjs', 'regl', 'sparkles', 'visualization', 'webgl'] | ['d3', 'dashboard', 'declarative', 'graph-library', 'interactive', 'jupyter-notebook', 'plotly', 'plotly-dash', 'plotlyjs', 'regl', 'sparkles', 'visualization', 'webgl'] | 2023-12-21 | [('bokeh/bokeh', 0.7521082758903503, 'viz', 1), ('vizzuhq/ipyvizzu', 0.7362504601478577, 'jupyter', 1), ('holoviz/panel', 0.7203231453895569, 'viz', 1), 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1 | 9 | 14 | 9 | 136 | 208 | 90 | 1.5 | 63 |
571 | perf | https://github.com/pybind/pybind11 | [] | null | [] | [] | null | null | null | pybind/pybind11 | pybind11 | 14,217 | 2,075 | 250 | C++ | https://pybind11.readthedocs.io/ | Seamless operability between C++11 and Python | pybind | 2024-01-14 | 2015-07-05 | 447 | 31.785053 | https://avatars.githubusercontent.com/u/17565521?v=4 | Seamless operability between C++11 and Python | ['bindings'] | ['bindings'] | 2024-01-13 | [('nvidia/cuda-python', 0.6058850288391113, 'ml', 0), ('marella/ctransformers', 0.5483258962631226, 'nlp', 0), ('pyo3/pyo3', 0.5454217791557312, 'util', 0), ('pyston/pyston', 0.5205539464950562, 'util', 0)] | 341 | 6 | null | 2.79 | 148 | 95 | 104 | 0 | 3 | 7 | 3 | 148 | 273 | 90 | 1.8 | 63 |
1,164 | llm | https://github.com/mayooear/gpt4-pdf-chatbot-langchain | [] | null | [] | [] | null | null | null | mayooear/gpt4-pdf-chatbot-langchain | gpt4-pdf-chatbot-langchain | 14,031 | 3,030 | 150 | TypeScript | https://www.youtube.com/watch?v=ih9PBGVVOO4 | GPT4 & LangChain Chatbot for large PDF docs | mayooear | 2024-01-14 | 2023-03-17 | 45 | 307.890282 | null | GPT4 & LangChain Chatbot for large PDF docs | ['gpt4', 'langchain', 'nextjs', 'openai', 'pdf', 'typescript'] | ['gpt4', 'langchain', 'nextjs', 'openai', 'pdf', 'typescript'] | 2023-11-13 | [('bhaskatripathi/pdfgpt', 0.6926714777946472, 'llm', 0), ('xtekky/gpt4free', 0.642866313457489, 'llm', 2), ('killianlucas/open-interpreter', 0.6425415277481079, 'llm', 0), ('run-llama/rags', 0.6243221163749695, 'llm', 1), ('openai/openai-cookbook', 0.59941166639328, 'ml', 1), ('h2oai/h2ogpt', 0.5983483195304871, 'llm', 1), ('langchain-ai/chat-langchain', 0.5839036107063293, 'llm', 0), ('embedchain/embedchain', 0.5652803182601929, 'llm', 0), ('microsoft/autogen', 0.5650250911712646, 'llm', 0), ('togethercomputer/openchatkit', 0.5483038425445557, 'nlp', 0), ('lm-sys/fastchat', 0.5297297239303589, 'llm', 0), ('imartinez/privategpt', 0.5235142707824707, 'llm', 1), ('minimaxir/simpleaichat', 0.5190370678901672, 'llm', 0), ('blinkdl/chatrwkv', 0.5159780979156494, 'llm', 0), ('larsbaunwall/bricky', 0.5141124725341797, 'llm', 2), ('mlc-ai/web-llm', 0.50135737657547, 'llm', 0)] | 3 | 2 | null | 0.4 | 64 | 40 | 10 | 2 | 0 | 0 | 0 | 64 | 87 | 90 | 1.4 | 63 |
902 | perf | https://github.com/exaloop/codon | [] | null | [] | [] | null | null | null | exaloop/codon | codon | 13,597 | 491 | 128 | C++ | https://docs.exaloop.io/codon | A high-performance, zero-overhead, extensible Python compiler using LLVM | exaloop | 2024-01-14 | 2021-09-27 | 122 | 111.320468 | https://avatars.githubusercontent.com/u/89494599?v=4 | A high-performance, zero-overhead, extensible Python compiler using LLVM | ['compiler', 'gpu-programming', 'high-performance', 'llvm', 'parallel-programming'] | ['compiler', 'gpu-programming', 'high-performance', 'llvm', 'parallel-programming'] | 2024-01-13 | [('numba/numba', 0.7364824414253235, 'perf', 2), ('lcompilers/lpython', 0.7257847189903259, 'util', 2), ('cython/cython', 0.7081640958786011, 'util', 0), ('pypy/pypy', 0.6885042786598206, 'util', 1), ('numba/llvmlite', 0.6857039332389832, 'util', 0), ('pyston/pyston', 0.6812407970428467, 'util', 0), ('nvidia/tensorrt-llm', 0.6340402364730835, 'viz', 0), ('fastai/fastcore', 0.6250977516174316, 'util', 0), ('google/jax', 0.6078891158103943, 'ml', 0), ('nvidia/warp', 0.603724479675293, 'sim', 0), ('joblib/joblib', 0.6015269160270691, 'util', 0), ('micropython/micropython', 0.5922623872756958, 'util', 0), ('oracle/graalpython', 0.5912636518478394, 'util', 0), ('citadel-ai/langcheck', 0.5882013440132141, 'llm', 0), ('ethereum/py-evm', 0.5648453235626221, 'crypto', 0), ('pytorch/glow', 0.5580657720565796, 'ml', 0), ('pympler/pympler', 0.5520622730255127, 'perf', 0), ('plasma-umass/scalene', 0.5468367338180542, 'profiling', 1), ('klen/py-frameworks-bench', 0.5465443730354309, 'perf', 0), ('ipython/ipyparallel', 0.5431182980537415, 'perf', 0), ('rustpython/rustpython', 0.5343741774559021, 'util', 1), ('pypa/hatch', 0.5342748761177063, 'util', 0), ('dosisod/refurb', 0.5304907560348511, 'util', 0), ('sail-sg/envpool', 0.5291399359703064, 'sim', 0), ('pytorch/pytorch', 0.5243420600891113, 'ml-dl', 0), ('python/cpython', 0.5238469839096069, 'util', 0), ('faster-cpython/tools', 0.518226146697998, 'perf', 0), ('hoffstadt/dearpygui', 0.5152654647827148, 'gui', 0), ('eth-sri/lmql', 0.5149834752082825, 'llm', 0), ('chainlit/chainlit', 0.5148961544036865, 'llm', 0), ('pytoolz/toolz', 0.514833390712738, 'util', 0), ('google/gin-config', 0.5136995911598206, 'util', 0), ('vllm-project/vllm', 0.5132838487625122, 'llm', 0), ('panda3d/panda3d', 0.5107043981552124, 'gamedev', 0), ('google/tf-quant-finance', 0.5077102780342102, 'finance', 1), ('pythonspeed/filprofiler', 0.5046871900558472, 'profiling', 0), ('microsoft/pycodegpt', 0.5030719041824341, 'llm', 0), ('intel/intel-extension-for-pytorch', 0.5024413466453552, 'perf', 0), ('facebookincubator/aitemplate', 0.5021023750305176, 'ml-dl', 0)] | 13 | 3 | null | 1 | 45 | 21 | 28 | 0 | 6 | 4 | 6 | 45 | 34 | 90 | 0.8 | 63 |
1,319 | llm | https://github.com/openlmlab/moss | ['language-model'] | null | [] | [] | null | null | null | openlmlab/moss | MOSS | 11,710 | 1,151 | 123 | Python | https://txsun1997.github.io/blogs/moss.html | An open-source tool-augmented conversational language model from Fudan University | openlmlab | 2024-01-14 | 2023-04-15 | 41 | 282.655172 | https://avatars.githubusercontent.com/u/127190579?v=4 | An open-source tool-augmented conversational language model from Fudan University | ['chatgpt', 'deep-learning', 'dialogue-systems', 'large-language-models', 'natural-language-processing', 'text-generation'] | ['chatgpt', 'deep-learning', 'dialogue-systems', 'language-model', 'large-language-models', 'natural-language-processing', 'text-generation'] | 2023-09-08 | [('lm-sys/fastchat', 0.6857122778892517, 'llm', 1), ('rasahq/rasa', 0.6797881126403809, 'llm', 1), ('deeppavlov/deeppavlov', 0.6669769287109375, 'nlp', 2), ('rcgai/simplyretrieve', 0.6414903998374939, 'llm', 2), ('nvidia/nemo', 0.640605628490448, 'nlp', 2), ('microsoft/autogen', 0.6363752484321594, 'llm', 1), ('next-gpt/next-gpt', 0.6183462738990784, 'llm', 2), ('embedchain/embedchain', 0.6122089624404907, 'llm', 1), ('krohling/bondai', 0.6103507876396179, 'llm', 0), ('aiwaves-cn/agents', 0.6080291271209717, 'nlp', 1), ('nomic-ai/gpt4all', 0.6058529615402222, 'llm', 1), ('run-llama/rags', 0.6012157797813416, 'llm', 1), ('fasteval/fasteval', 0.593492329120636, 'llm', 0), ('lupantech/chameleon-llm', 0.5891066789627075, 'llm', 2), ('killianlucas/open-interpreter', 0.5889337062835693, 'llm', 1), ('guidance-ai/guidance', 0.5859184861183167, 'llm', 2), ('thudm/chatglm2-6b', 0.5803049802780151, 'llm', 1), ('xtekky/gpt4free', 0.5782349705696106, 'llm', 2), ('whu-zqh/chatgpt-vs.-bert', 0.5750217437744141, 'llm', 1), ('mlc-ai/web-llm', 0.5738821029663086, 'llm', 3), ('argilla-io/argilla', 0.5668735504150391, 'nlp', 1), ('blinkdl/chatrwkv', 0.5662409067153931, 'llm', 2), ('huggingface/text-generation-inference', 0.5647656917572021, 'llm', 1), ('conceptofmind/toolformer', 0.5642003417015076, 'llm', 1), ('deepset-ai/haystack', 0.5615432262420654, 'llm', 3), ('facebookresearch/parlai', 0.5612495541572571, 'nlp', 0), ('infinitylogesh/mutate', 0.5608090758323669, 'nlp', 2), ('thudm/chatglm-6b', 0.556516170501709, 'llm', 1), ('reasoning-machines/pal', 0.5542696714401245, 'llm', 2), ('chatarena/chatarena', 0.5541568398475647, 'llm', 3), ('databrickslabs/dolly', 0.5508648157119751, 'llm', 0), ('ai21labs/lm-evaluation', 0.5499148368835449, 'llm', 1), ('lianjiatech/belle', 0.5496982336044312, 'llm', 0), ('night-chen/toolqa', 0.549114465713501, 'llm', 1), ('minimaxir/gpt-2-simple', 0.5483125448226929, 'llm', 1), ('allenai/allennlp', 0.548026978969574, 'nlp', 2), ('baichuan-inc/baichuan-13b', 0.5460556149482727, 'llm', 3), ('gunthercox/chatterbot-corpus', 0.5456989407539368, 'nlp', 0), ('microsoft/generative-ai-for-beginners', 0.5399401783943176, 'study', 2), ('weaviate/verba', 0.5387402772903442, 'llm', 0), ('eugeneyan/obsidian-copilot', 0.5385111570358276, 'llm', 1), ('hannibal046/awesome-llm', 0.5380090475082397, 'study', 1), ('bigscience-workshop/promptsource', 0.5367189049720764, 'nlp', 1), ('togethercomputer/openchatkit', 0.5363262295722961, 'nlp', 0), ('ctlllll/llm-toolmaker', 0.5362043976783752, 'llm', 1), ('llmware-ai/llmware', 0.5356535911560059, 'llm', 1), ('young-geng/easylm', 0.5339535474777222, 'llm', 4), ('minimaxir/simpleaichat', 0.5309569835662842, 'llm', 1), ('openbmb/toolbench', 0.5276908278465271, 'llm', 0), ('langchain-ai/chat-langchain', 0.5243722200393677, 'llm', 0), ('hwchase17/langchain', 0.5230026245117188, 'llm', 1), ('ai21labs/in-context-ralm', 0.5220905542373657, 'llm', 1), ('srush/minichain', 0.5213707089424133, 'llm', 0), ('oobabooga/text-generation-webui', 0.5163723230361938, 'llm', 1), ('minimaxir/aitextgen', 0.5120126008987427, 'llm', 0), ('yueyu1030/attrprompt', 0.5103434920310974, 'llm', 2), ('lucidrains/toolformer-pytorch', 0.508660614490509, 'llm', 2), ('freedomintelligence/llmzoo', 0.5085688233375549, 'llm', 1), ('jalammar/ecco', 0.5079621076583862, 'ml-interpretability', 1), ('facebookresearch/seamless_communication', 0.5070318579673767, 'nlp', 0), ('laion-ai/open-assistant', 0.5062494874000549, 'llm', 2), ('explosion/spacy-llm', 0.5049393773078918, 'llm', 2), ('ofa-sys/ofa', 0.5047501921653748, 'llm', 0), ('nvidia/nemo-guardrails', 0.504492461681366, 'llm', 1), ('promptslab/awesome-prompt-engineering', 0.5036895871162415, 'study', 2), ('paddlepaddle/paddlenlp', 0.5025514364242554, 'llm', 0)] | 17 | 3 | null | 3.42 | 13 | 2 | 9 | 4 | 0 | 0 | 0 | 13 | 13 | 90 | 1 | 63 |
644 | profiling | https://github.com/plasma-umass/scalene | [] | null | [] | [] | 1 | null | null | plasma-umass/scalene | scalene | 10,488 | 362 | 87 | JavaScript | null | Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals | plasma-umass | 2024-01-14 | 2019-12-17 | 215 | 48.781395 | https://avatars.githubusercontent.com/u/1880823?v=4 | Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals | ['cpu', 'cpu-profiling', 'gpu', 'gpu-programming', 'memory-allocation', 'memory-consumption', 'performance-analysis', 'performance-cpu', 'profiler', 'profiles-memory', 'profiling', 'python-profilers', 'scalene'] | ['cpu', 'cpu-profiling', 'gpu', 'gpu-programming', 'memory-allocation', 'memory-consumption', 'performance-analysis', 'performance-cpu', 'profiler', 'profiles-memory', 'profiling', 'python-profilers', 'scalene'] | 2024-01-11 | [('ray-project/ray', 0.6044383645057678, 'ml-ops', 0), ('pythonspeed/filprofiler', 0.6020299196243286, 'profiling', 0), ('micropython/micropython', 0.6017813086509705, 'util', 0), ('intel/intel-extension-for-pytorch', 0.5931693315505981, 'perf', 0), ('cython/cython', 0.5566608905792236, 'util', 0), ('pytorch/glow', 0.5508031249046326, 'ml', 0), ('sumerc/yappi', 0.549071192741394, 'profiling', 1), ('pytorch/pytorch', 0.5483222007751465, 'ml-dl', 1), ('exaloop/codon', 0.5468367338180542, 'perf', 1), ('google/jax', 0.5463865399360657, 'ml', 0), ('blackhc/toma', 0.545809268951416, 'ml-dl', 1), ('nvidia/tensorrt-llm', 0.53840172290802, 'viz', 1), ('fastai/fastcore', 0.5373175144195557, 'util', 0), ('benfred/py-spy', 0.533981204032898, 'profiling', 3), ('joblib/joblib', 0.5323008298873901, 'util', 0), ('gradio-app/gradio', 0.5309175252914429, 'viz', 0), ('pytorchlightning/pytorch-lightning', 0.5295047760009766, 'ml-dl', 0), ('spotify/annoy', 0.5279016494750977, 'ml', 0), ('google/vizier', 0.5277619957923889, 'ml', 0), ('numpy/numpy', 0.5247296094894409, 'math', 0), ('determined-ai/determined', 0.524320125579834, 'ml-ops', 0), ('wandb/client', 0.5181810855865479, 'ml', 0), ('google/tf-quant-finance', 0.5155574083328247, 'finance', 1), ('pyston/pyston', 0.5100093483924866, 'util', 0), ('google/gin-config', 0.5083065032958984, 'util', 0), ('facebookincubator/aitemplate', 0.5074851512908936, 'ml-dl', 0), ('karpathy/micrograd', 0.5055549740791321, 'study', 0), ('microsoft/deepspeed', 0.5038928389549255, 'ml-dl', 1), ('microsoft/olive', 0.503036618232727, 'ml', 1), ('reloadware/reloadium', 0.5005995035171509, 'profiling', 0), ('klen/py-frameworks-bench', 0.500389039516449, 'perf', 0), ('mrdbourke/m1-machine-learning-test', 0.5002366900444031, 'ml', 0)] | 44 | 6 | null | 3.65 | 52 | 27 | 50 | 0 | 19 | 15 | 19 | 52 | 55 | 90 | 1.1 | 63 |
93 | ml-ops | https://github.com/ludwig-ai/ludwig | ['llm-training'] | null | [] | [] | null | null | null | ludwig-ai/ludwig | ludwig | 10,390 | 1,150 | 190 | Python | http://ludwig.ai | Low-code framework for building custom LLMs, neural networks, and other AI models | ludwig-ai | 2024-01-13 | 2018-12-27 | 265 | 39.102151 | https://avatars.githubusercontent.com/u/65477820?v=4 | Low-code framework for building custom LLMs, neural networks, and other AI models | ['computer-vision', 'data-centric', 'data-science', 'deep', 'deep-learning', 'deeplearning', 'fine-tuning', 'learning', 'llama', 'llama2', 'llm', 'llm-training', 'machine-learning', 'machinelearning', 'mistral', 'ml', 'natural-language', 'natural-language-processing', 'neural-network', 'pytorch'] | ['computer-vision', 'data-centric', 'data-science', 'deep', 'deep-learning', 'deeplearning', 'fine-tuning', 'learning', 'llama', 'llama2', 'llm', 'llm-training', 'machine-learning', 'machinelearning', 'mistral', 'ml', 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1,624 | util | https://github.com/nuitka/nuitka | [] | null | [] | [] | null | null | null | nuitka/nuitka | Nuitka | 10,305 | 563 | 135 | Python | http://nuitka.net | Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module. | nuitka | 2024-01-14 | 2013-04-23 | 562 | 18.336299 | https://avatars.githubusercontent.com/u/43496036?v=4 | Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module. | ['compiler', 'nuitka', 'packaging-tool', 'performance', 'programming', 'python-compiler'] | ['compiler', 'nuitka', 'packaging-tool', 'performance', 'programming', 'python-compiler'] | 2024-01-12 | [('chrismattmann/tika-python', 0.5718207955360413, 'nlp', 0), ('numerai/numerox', 0.5074256062507629, 'finance', 0), ('pypy/pypy', 0.5013567209243774, 'util', 1)] | 166 | 4 | null | 89.88 | 1,753 | 1,685 | 131 | 0 | 0 | 34 | 34 | 1,753 | 851 | 90 | 0.5 | 63 |
1,066 | data | https://github.com/bigscience-workshop/petals | [] | null | [] | [] | null | null | null | bigscience-workshop/petals | petals | 8,241 | 423 | 87 | Python | https://petals.dev | 🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading | bigscience-workshop | 2024-01-14 | 2022-06-12 | 85 | 96.628141 | https://avatars.githubusercontent.com/u/82455566?v=4 | 🌸 Run LLMs at home, BitTorrent-style. 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457 | ml-ops | https://github.com/dbt-labs/dbt-core | [] | null | [] | [] | null | null | null | dbt-labs/dbt-core | dbt-core | 8,100 | 1,422 | 134 | Python | https://getdbt.com | dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. | dbt-labs | 2024-01-14 | 2016-03-10 | 411 | 19.673838 | https://avatars.githubusercontent.com/u/18339788?v=4 | dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. | ['analytics', 'business-intelligence', 'data-modeling', 'dbt-viewpoint', 'elt', 'pypa', 'slack'] | ['analytics', 'business-intelligence', 'data-modeling', 'dbt-viewpoint', 'elt', 'pypa', 'slack'] | 2024-01-12 | [('mage-ai/mage-ai', 0.5732520818710327, 'ml-ops', 1), ('airbytehq/airbyte', 0.5581380724906921, 'data', 1), ('datafold/data-diff', 0.550411581993103, 'data', 0), ('dlt-hub/dlt', 0.5388659834861755, 'data', 1), ('databricks/dbt-databricks', 0.5302814841270447, 'data', 0), ('dagster-io/dagster', 0.5295764803886414, 'ml-ops', 1), ('saulpw/visidata', 0.5234029293060303, 'term', 0), ('great-expectations/great_expectations', 0.5088808536529541, 'ml-ops', 0), ('google/ml-metadata', 0.5018987655639648, 'ml-ops', 0)] | 302 | 3 | null | 12.71 | 777 | 483 | 96 | 0 | 73 | 28 | 73 | 777 | 1,463 | 90 | 1.9 | 63 |
66 | ml | https://github.com/pycaret/pycaret | [] | null | [] | [] | null | null | null | pycaret/pycaret | pycaret | 8,084 | 1,715 | 133 | Jupyter Notebook | https://www.pycaret.org | An open-source, low-code machine learning library in Python | pycaret | 2024-01-14 | 2019-11-23 | 218 | 37.00981 | https://avatars.githubusercontent.com/u/58118658?v=4 | An open-source, low-code machine learning library in Python | ['anomaly-detection', 'citizen-data-scientists', 'classification', 'clustering', 'data-science', 'gpu', 'machine-learning', 'ml', 'pycaret', 'regression', 'time-series'] | ['anomaly-detection', 'citizen-data-scientists', 'classification', 'clustering', 'data-science', 'gpu', 'machine-learning', 'ml', 'pycaret', 'regression', 'time-series'] | 2023-12-14 | [('yzhao062/pyod', 0.7633078694343567, 'data', 3), ('unit8co/darts', 0.7233750820159912, 'time-series', 4), ('rasbt/mlxtend', 0.7207165956497192, 'ml', 2), ('featurelabs/featuretools', 0.6861603856086731, 'ml', 2), 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162 | ml | https://github.com/wandb/client | [] | null | [] | [] | null | null | null | wandb/client | wandb | 7,706 | 594 | 55 | Python | https://wandb.ai | 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API. | wandb | 2024-01-14 | 2017-03-24 | 357 | 21.550939 | https://avatars.githubusercontent.com/u/26401354?v=4 | 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API. | ['collaboration', 'data-science', 'data-versioning', 'deep-learning', 'experiment-track', 'hyperparameter-optimization', 'hyperparameter-search', 'hyperparameter-tuning', 'jax', 'keras', 'machine-learning', 'ml-platform', 'mlops', 'model-versioning', 'pytorch', 'reinforcement-learning', 'reproducibility', 'tensorflow'] | ['collaboration', 'data-science', 'data-versioning', 'deep-learning', 'experiment-track', 'hyperparameter-optimization', 'hyperparameter-search', 'hyperparameter-tuning', 'jax', 'keras', 'machine-learning', 'ml-platform', 'mlops', 'model-versioning', 'pytorch', 'reinforcement-learning', 'reproducibility', 'tensorflow'] | 2024-01-12 | [('aimhubio/aim', 0.696733832359314, 'ml-ops', 5), ('determined-ai/determined', 0.6777682900428772, 'ml-ops', 11), ('polyaxon/polyaxon', 0.6643576622009277, 'ml-ops', 9), ('polyaxon/datatile', 0.6632310748100281, 'pandas', 4), ('gradio-app/gradio', 0.6344223618507385, 'viz', 3), 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1,571 | nlp | https://github.com/facebookresearch/nougat | ['documents', 'pdf-parser', 'academic', 'latex'] | null | [] | [] | null | null | null | facebookresearch/nougat | nougat | 7,391 | 462 | 60 | Python | https://facebookresearch.github.io/nougat/ | Implementation of Nougat Neural Optical Understanding for Academic Documents | facebookresearch | 2024-01-14 | 2023-06-07 | 33 | 218.299578 | https://avatars.githubusercontent.com/u/16943930?v=4 | Implementation of Nougat Neural Optical Understanding for Academic Documents | [] | ['academic', 'documents', 'latex', 'pdf-parser'] | 2023-10-04 | [] | 15 | 2 | null | 1.12 | 59 | 16 | 7 | 3 | 2 | 3 | 2 | 59 | 89 | 90 | 1.5 | 63 |
1,537 | llm | https://github.com/lianjiatech/belle | [] | null | [] | [] | null | null | null | lianjiatech/belle | BELLE | 7,155 | 711 | 105 | HTML | null | BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型） | lianjiatech | 2024-01-14 | 2023-03-17 | 45 | 157.00627 | https://avatars.githubusercontent.com/u/14540911?v=4 | BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型） | ['bloom', 'chinese-nlp', 'gpt-evaluation', 'gpt-q', 'instruct-finetune', 'instruct-gpt', 'instruction-set', 'llama', 'lora', 'open-models'] | ['bloom', 'chinese-nlp', 'gpt-evaluation', 'gpt-q', 'instruct-finetune', 'instruct-gpt', 'instruction-set', 'llama', 'lora', 'open-models'] | 2023-12-29 | [('hannibal046/awesome-llm', 0.8117328882217407, 'study', 0), ('microsoft/autogen', 0.6912463903427124, 'llm', 0), ('ctlllll/llm-toolmaker', 0.6910099983215332, 'llm', 0), ('ai21labs/lm-evaluation', 0.6819735169410706, 'llm', 0), ('bobazooba/xllm', 0.6800654530525208, 'llm', 1), ('baichuan-inc/baichuan-13b', 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1,449 | util | https://github.com/pdm-project/pdm | ['package-manager', 'packaging'] | null | [] | [] | null | null | null | pdm-project/pdm | pdm | 5,927 | 302 | 31 | Python | https://pdm-project.org | A modern Python package and dependency manager supporting the latest PEP standards | pdm-project | 2024-01-14 | 2019-12-27 | 213 | 27.751839 | https://avatars.githubusercontent.com/u/59549022?v=4 | A modern Python package and dependency manager supporting the latest PEP standards | ['package-manager', 'packaging', 'pep582', 'pep621', 'workflow'] | ['package-manager', 'packaging', 'pep582', 'pep621', 'workflow'] | 2024-01-12 | [('mitsuhiko/rye', 0.7408201694488525, 'util', 2), ('indygreg/pyoxidizer', 0.7249577045440674, 'util', 2), ('python-poetry/poetry', 0.7060061097145081, 'util', 2), ('pypa/hatch', 0.6953819394111633, 'util', 2), ('pomponchik/instld', 0.6940727829933167, 'util', 1), ('pypi/warehouse', 0.6904469728469849, 'util', 0), ('pypa/flit', 0.6415485143661499, 'util', 2), ('jazzband/pip-tools', 0.6316167116165161, 'util', 1), ('pyodide/micropip', 0.6069954037666321, 'util', 0), ('mamba-org/mamba', 0.6015645861625671, 'util', 2), ('thoth-station/micropipenv', 0.5940836071968079, 'util', 0), ('pytoolz/toolz', 0.592634379863739, 'util', 0), ('hhatto/autopep8', 0.5722745656967163, 'util', 0), ('regebro/pyroma', 0.568504810333252, 'util', 1), ('pypa/pipenv', 0.5644690990447998, 'util', 1), ('tezromach/python-package-template', 0.5643466114997864, 'template', 0), ('urwid/urwid', 0.5620359778404236, 'term', 0), ('dosisod/refurb', 0.5603682398796082, 'util', 0), ('spack/spack', 0.5586650371551514, 'util', 1), ('tox-dev/pipdeptree', 0.5571689605712891, 'util', 0), ('pypa/installer', 0.5561202168464661, 'util', 0), ('hoffstadt/dearpygui', 0.5533838868141174, 'gui', 0), ('trailofbits/pip-audit', 0.54820716381073, 'security', 0), ('pypy/pypy', 0.5482062101364136, 'util', 0), ('conda/conda', 0.5474826097488403, 'util', 2), ('tiangolo/poetry-version-plugin', 0.54221111536026, 'util', 1), ('pyupio/safety', 0.5419641733169556, 'security', 0), ('libtcod/python-tcod', 0.5411107540130615, 'gamedev', 0), ('malloydata/malloy-py', 0.5352970957756042, 'data', 0), ('eleutherai/pyfra', 0.5340529680252075, 'ml', 0), ('omry/omegaconf', 0.5336859822273254, 'util', 0), ('pyo3/maturin', 0.5319200754165649, 'util', 1), ('pyscaffold/pyscaffold', 0.531360924243927, 'template', 0), ('pyston/pyston', 0.530032217502594, 'util', 0), ('prompt-toolkit/ptpython', 0.518380880355835, 'util', 0), ('allrod5/injectable', 0.5183610320091248, 'util', 0), ('ofek/pyapp', 0.514813244342804, 'util', 1), ('python-injector/injector', 0.5129967927932739, 'util', 0), ('bndr/pipreqs', 0.5109939575195312, 'util', 0), ('pyenv/pyenv', 0.5091418027877808, 'util', 0), ('psf/black', 0.5081842541694641, 'util', 0), ('grahamdumpleton/wrapt', 0.5066951513290405, 'util', 0), ('google/python-fire', 0.5054830312728882, 'term', 0), ('primal100/pybitcointools', 0.505200207233429, 'crypto', 0), ('sqlalchemy/mako', 0.5048580765724182, 'template', 0), ('eugeneyan/python-collab-template', 0.5047013163566589, 'template', 0), ('ethtx/ethtx', 0.5046972632408142, 'crypto', 0), ('python/cpython', 0.5036362409591675, 'util', 0), ('python-rope/rope', 0.5023258328437805, 'util', 0), ('tedivm/robs_awesome_python_template', 0.5013588070869446, 'template', 0), ('linkedin/shiv', 0.5008074641227722, 'util', 0)] | 161 | 4 | null | 8.96 | 241 | 219 | 49 | 0 | 41 | 46 | 41 | 241 | 508 | 90 | 2.1 | 63 |
1,259 | util | https://github.com/timdettmers/bitsandbytes | ['cuda'] | null | [] | [] | null | null | null | timdettmers/bitsandbytes | bitsandbytes | 4,678 | 503 | 43 | Python | null | Accessible large language models via k-bit quantization for PyTorch. | timdettmers | 2024-01-14 | 2021-06-04 | 138 | 33.758763 | null | Accessible large language models via k-bit quantization for PyTorch. | [] | ['cuda'] | 2024-01-12 | [('artidoro/qlora', 0.6154015064239502, 'llm', 0), ('squeezeailab/squeezellm', 0.6107233166694641, 'llm', 0), ('allenai/allennlp', 0.5652725100517273, 'nlp', 0), ('cqcl/lambeq', 0.5420622229576111, 'nlp', 0), ('rentruewang/koila', 0.5362823009490967, 'ml', 0), ('sjtu-ipads/powerinfer', 0.5349003076553345, 'llm', 0), ('intel/intel-extension-for-pytorch', 0.5321269631385803, 'perf', 0), ('opengvlab/omniquant', 0.5289829969406128, 'llm', 0), ('juncongmoo/pyllama', 0.5255274772644043, 'llm', 0), ('ggerganov/ggml', 0.5234319567680359, 'ml', 0), ('jonasgeiping/cramming', 0.5229673981666565, 'nlp', 0), ('nvidia/apex', 0.5227283239364624, 'ml-dl', 0), ('pytorch/ignite', 0.5188927054405212, 'ml-dl', 0), ('huggingface/transformers', 0.5178513526916504, 'nlp', 0), ('hannibal046/awesome-llm', 0.5172896385192871, 'study', 0), ('baichuan-inc/baichuan-13b', 0.5144120454788208, 'llm', 0), ('cvxgrp/pymde', 0.509398341178894, 'ml', 1), ('salesforce/blip', 0.5067077875137329, 'diffusion', 0), ('huggingface/accelerate', 0.5063002705574036, 'ml', 0), ('pytorch/data', 0.5031000375747681, 'data', 0), ('bytedance/lightseq', 0.5029526948928833, 'nlp', 1), ('arogozhnikov/einops', 0.5005117654800415, 'ml-dl', 0)] | 56 | 6 | null | 5.06 | 719 | 616 | 32 | 0 | 6 | 5 | 6 | 719 | 1,336 | 90 | 1.9 | 63 |
1,769 | data | https://github.com/tobymao/sqlglot | [] | null | [] | [] | 1 | null | null | tobymao/sqlglot | sqlglot | 4,500 | 479 | 33 | Python | https://sqlglot.com/ | Python SQL Parser and Transpiler | tobymao | 2024-01-14 | 2021-03-13 | 150 | 29.91453 | null | Python SQL Parser and Transpiler | ['bigquery', 'clickhouse', 'databricks', 'duckdb', 'hive', 'mysql', 'optimizer', 'parser', 'postgres', 'presto', 'redshift', 'snowflake', 'spark', 'sql', 'sqlite', 'sqlparser', 'transpiler', 'trino', 'tsql'] | ['bigquery', 'clickhouse', 'databricks', 'duckdb', 'hive', 'mysql', 'optimizer', 'parser', 'postgres', 'presto', 'redshift', 'snowflake', 'spark', 'sql', 'sqlite', 'sqlparser', 'transpiler', 'trino', 'tsql'] | 2024-01-14 | [('ibis-project/ibis', 0.7856696248054504, 'data', 8), ('macbre/sql-metadata', 0.6693900227546692, 'data', 3), ('tiangolo/sqlmodel', 0.6654618382453918, 'data', 1), ('andialbrecht/sqlparse', 0.6332684755325317, 'data', 0), ('pyparsing/pyparsing', 0.6120659708976746, 'util', 0), ('machow/siuba', 0.6064596176147461, 'pandas', 1), ('sqlalchemy/sqlalchemy', 0.6049283742904663, 'data', 1), ('fastai/fastcore', 0.5786949396133423, 'util', 0), ('malloydata/malloy-py', 0.5748046040534973, 'data', 1), ('aws/aws-sdk-pandas', 0.5701399445533752, 'pandas', 2), ('kayak/pypika', 0.5631858706474304, 'data', 1), ('datafold/data-diff', 0.5574495196342468, 'data', 5), ('mcfunley/pugsql', 0.5487765073776245, 'data', 1), ('pola-rs/polars', 0.5481932163238525, 'pandas', 0), ('sfu-db/connector-x', 0.5419861674308777, 'data', 1), ('coleifer/peewee', 0.5414004325866699, 'data', 1), ('fugue-project/fugue', 0.5296240448951721, 'pandas', 3), ('strawberry-graphql/strawberry', 0.5215062499046326, 'web', 0), ('airbytehq/airbyte', 0.5210596919059753, 'data', 4), ('dagworks-inc/hamilton', 0.5160204768180847, 'ml-ops', 0), ('pytoolz/toolz', 0.5141063928604126, 'util', 0), ('astronomer/astro-sdk', 0.5131558179855347, 'ml-ops', 5), ('ploomber/ploomber', 0.5114932656288147, 'ml-ops', 0), ('apache/spark', 0.5114732980728149, 'data', 2), ('pandas-dev/pandas', 0.5091575384140015, 'pandas', 0), ('databricks/dbt-databricks', 0.5069236755371094, 'data', 2), ('mage-ai/mage-ai', 0.5064417123794556, 'ml-ops', 2), ('unionai-oss/pandera', 0.5052539706230164, 'pandas', 0), ('cython/cython', 0.5022580623626709, 'util', 0), ('vaexio/vaex', 0.5004581809043884, 'perf', 0)] | 117 | 3 | null | 34.85 | 410 | 406 | 35 | 0 | 0 | 163 | 163 | 411 | 470 | 90 | 1.1 | 63 |
785 | ml-dl | https://github.com/facebookincubator/aitemplate | [] | null | [] | [] | null | null | null | facebookincubator/aitemplate | AITemplate | 4,354 | 349 | 84 | Python | null | AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference. | facebookincubator | 2024-01-13 | 2022-07-15 | 80 | 54.039007 | https://avatars.githubusercontent.com/u/19538647?v=4 | AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference. | [] | [] | 2024-01-06 | [('nvidia/tensorrt-llm', 0.5429112315177917, 'viz', 0), ('pytorch/glow', 0.542003870010376, 'ml', 0), ('pytorch/pytorch', 0.5403209328651428, 'ml-dl', 0), ('plasma-umass/scalene', 0.5074851512908936, 'profiling', 0), ('nvidia/warp', 0.502746045589447, 'sim', 0), ('exaloop/codon', 0.5021023750305176, 'perf', 0)] | 89 | 4 | null | 12.44 | 42 | 28 | 18 | 0 | 1 | 1 | 1 | 42 | 127 | 90 | 3 | 63 |
1,583 | nlp | https://github.com/aiwaves-cn/agents | [] | null | [] | [] | null | null | null | aiwaves-cn/agents | agents | 4,205 | 307 | 58 | Python | http://www.aiwaves-agents.com/ | An Open-source Framework for Autonomous Language Agents | aiwaves-cn | 2024-01-13 | 2023-07-18 | 28 | 150.178571 | https://avatars.githubusercontent.com/u/129118469?v=4 | An Open-source Framework for Autonomous Language Agents | ['autonomous-agents', 'language-model', 'llm'] | ['autonomous-agents', 'language-model', 'llm'] | 2023-12-04 | [('nomic-ai/gpt4all', 0.6714950799942017, 'llm', 1), ('krohling/bondai', 0.6704409718513489, 'llm', 1), ('rasahq/rasa', 0.6561240553855896, 'llm', 0), ('jina-ai/thinkgpt', 0.6464569568634033, 'llm', 1), ('lm-sys/fastchat', 0.6372155547142029, 'llm', 1), ('microsoft/autogen', 0.6282492280006409, 'llm', 1), ('openlmlab/moss', 0.6080291271209717, 'llm', 1), ('embedchain/embedchain', 0.6022089123725891, 'llm', 1), ('argilla-io/argilla', 0.5958381295204163, 'nlp', 1), ('noahshinn/reflexion', 0.5806130170822144, 'llm', 1), ('operand/agency', 0.5783196687698364, 'llm', 2), ('minedojo/voyager', 0.5751522183418274, 'llm', 0), ('explosion/spacy-llm', 0.5685261487960815, 'llm', 1), ('tigerlab-ai/tiger', 0.5588130950927734, 'llm', 1), ('juncongmoo/pyllama', 0.5563294887542725, 'llm', 0), ('infinitylogesh/mutate', 0.5541864037513733, 'nlp', 1), ('langchain-ai/langgraph', 0.5516238808631897, 'llm', 0), ('young-geng/easylm', 0.5498647689819336, 'llm', 1), ('nebuly-ai/nebullvm', 0.5476635098457336, 'perf', 1), ('conceptofmind/toolformer', 0.5445042252540588, 'llm', 1), ('lupantech/chameleon-llm', 0.5420612692832947, 'llm', 2), ('chatarena/chatarena', 0.5419332385063171, 'llm', 0), ('humanoidagents/humanoidagents', 0.5400265455245972, 'sim', 1), ('deepset-ai/haystack', 0.5381879806518555, 'llm', 1), ('hwchase17/langchain', 0.536536693572998, 'llm', 1), ('salesforce/xgen', 0.5333874225616455, 'llm', 2), ('google-research/language', 0.5324529409408569, 'nlp', 0), ('mooler0410/llmspracticalguide', 0.5291845202445984, 'study', 0), ('guardrails-ai/guardrails', 0.528048038482666, 'llm', 1), ('deeppavlov/deeppavlov', 0.5271100997924805, 'nlp', 0), ('hannibal046/awesome-llm', 0.5250198245048523, 'study', 1), ('cg123/mergekit', 0.5241085886955261, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5234825611114502, 'llm', 1), ('run-llama/rags', 0.5222904682159424, 'llm', 1), ('ibm/dromedary', 0.5198720097541809, 'llm', 1), ('fasteval/fasteval', 0.5190715789794922, 'llm', 1), ('thudm/chatglm2-6b', 0.5184250473976135, 'llm', 1), ('nvidia/nemo-guardrails', 0.5130923986434937, 'llm', 1), ('zacwellmer/worldmodels', 0.5116593241691589, 'ml-rl', 0), ('databrickslabs/dolly', 0.5108225345611572, 'llm', 0), ('eleutherai/the-pile', 0.5101150274276733, 'data', 1), ('allenai/allennlp', 0.5092148184776306, 'nlp', 0), ('night-chen/toolqa', 0.5083682537078857, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5078116059303284, 'nlp', 0), ('prefecthq/marvin', 0.506673276424408, 'nlp', 1), ('mlc-ai/mlc-llm', 0.5054627060890198, 'llm', 2), ('guidance-ai/guidance', 0.5045157670974731, 'llm', 1), ('transformeroptimus/superagi', 0.5044564604759216, 'llm', 2), ('freedomintelligence/llmzoo', 0.5030314922332764, 'llm', 1), ('reasoning-machines/pal', 0.5023298263549805, 'llm', 1), ('openlm-research/open_llama', 0.5005034804344177, 'llm', 1), ('rcgai/simplyretrieve', 0.5003217458724976, 'llm', 0)] | 23 | 3 | null | 20.21 | 47 | 37 | 6 | 1 | 0 | 0 | 0 | 47 | 50 | 90 | 1.1 | 63 |
1,246 | ml-dl | https://github.com/deci-ai/super-gradients | [] | null | [] | [] | null | null | null | deci-ai/super-gradients | super-gradients | 4,073 | 452 | 41 | Jupyter Notebook | https://www.supergradients.com | Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. | deci-ai | 2024-01-14 | 2021-11-28 | 113 | 35.953342 | https://avatars.githubusercontent.com/u/56918593?v=4 | Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. | ['computer-vision', 'deep-learning', 'image-classification', 'imagenet', 'neural-network', 'object-detection', 'pretrained-models', 'pretrained-weights', 'pytorch', 'semantic-segmentation', 'transfer-learning'] | ['computer-vision', 'deep-learning', 'image-classification', 'imagenet', 'neural-network', 'object-detection', 'pretrained-models', 'pretrained-weights', 'pytorch', 'semantic-segmentation', 'transfer-learning'] | 2024-01-12 | [('roboflow/notebooks', 0.8082399368286133, 'study', 5), ('roboflow/supervision', 0.6838550567626953, 'ml', 4), ('facebookresearch/vissl', 0.6394485831260681, 'ml', 0), ('google-research/maxvit', 0.6301395893096924, 'ml', 2), ('nvlabs/gcvit', 0.6253355145454407, 'diffusion', 4), ('lucidrains/vit-pytorch', 0.62143474817276, 'ml-dl', 2), ('open-mmlab/mmdetection', 0.6168127655982971, 'ml', 2), ('kornia/kornia', 0.6162040829658508, 'ml-dl', 4), ('rwightman/pytorch-image-models', 0.612806499004364, 'ml-dl', 3), ('lightly-ai/lightly', 0.610939621925354, 'ml', 3), ('open-mmlab/mmsegmentation', 0.5933340787887573, 'ml', 2), ('tensorflow/tensorflow', 0.5904759764671326, 'ml-dl', 2), ('megvii-basedetection/yolox', 0.5785552859306335, 'ml', 3), ('keras-team/keras-cv', 0.5779148936271667, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5777014493942261, 'ml-dl', 2), ('open-mmlab/mmcv', 0.5693687796592712, 'ml', 1), ('lutzroeder/netron', 0.5625087022781372, 'ml', 3), ('blakeblackshear/frigate', 0.5583767294883728, 'util', 1), ('mdbloice/augmentor', 0.5568101406097412, 'ml', 1), ('salesforce/blip', 0.5560441613197327, 'diffusion', 0), ('albumentations-team/albumentations', 0.5558651685714722, 'ml-dl', 3), ('microsoft/swin-transformer', 0.5506076812744141, 'ml', 4), ('azavea/raster-vision', 0.5499731302261353, 'gis', 5), ('kevinmusgrave/pytorch-metric-learning', 0.5495540499687195, 'ml', 3), ('huggingface/datasets', 0.5464844107627869, 'nlp', 3), ('pytorch/ignite', 0.5459545850753784, 'ml-dl', 3), ('matterport/mask_rcnn', 0.5377986431121826, 'ml-dl', 1), ('hysts/pytorch_image_classification', 0.5351361632347107, 'ml-dl', 3), ('towhee-io/towhee', 0.5340181589126587, 'ml-ops', 1), ('microsoft/torchgeo', 0.5279808640480042, 'gis', 3), ('lucidrains/imagen-pytorch', 0.5232393145561218, 'ml-dl', 1), ('open-mmlab/mmediting', 0.5221906900405884, 'ml', 3), ('google/automl', 0.5212241411209106, 'ml', 1), ('facebookresearch/detectron2', 0.5197049379348755, 'ml-dl', 0), ('idea-research/groundingdino', 0.5182757377624512, 'diffusion', 1), ('microsoft/onnxruntime', 0.5170263051986694, 'ml', 2), ('oml-team/open-metric-learning', 0.5170210599899292, 'ml', 3), ('neuralmagic/sparseml', 0.5168516039848328, 'ml-dl', 4), ('aleju/imgaug', 0.5129750370979309, 'ml', 1), ('ludwig-ai/ludwig', 0.5076872706413269, 'ml-ops', 4), ('mlflow/mlflow', 0.505067765712738, 'ml-ops', 0), ('activeloopai/deeplake', 0.5050042867660522, 'ml-ops', 3), ('mosaicml/composer', 0.5038636326789856, 'ml-dl', 3), ('horovod/horovod', 0.5012701749801636, 'ml-ops', 2), ('christoschristofidis/awesome-deep-learning', 0.5002260804176331, 'study', 2)] | 52 | 5 | null | 9.79 | 289 | 256 | 26 | 0 | 14 | 457 | 14 | 289 | 401 | 90 | 1.4 | 63 |
1,111 | llm | https://github.com/mmabrouk/chatgpt-wrapper | [] | null | [] | [] | null | null | null | mmabrouk/chatgpt-wrapper | llm-workflow-engine | 3,541 | 463 | 42 | Python | null | Power CLI and Workflow manager for LLMs (core package) | mmabrouk | 2024-01-14 | 2022-12-03 | 60 | 58.598109 | https://avatars.githubusercontent.com/u/134339574?v=4 | Power CLI and Workflow manager for LLMs (core package) | ['chatbot', 'chatgpt', 'gpt-3', 'gpt3', 'gpt4', 'llm', 'openai'] | ['chatbot', 'chatgpt', 'gpt-3', 'gpt3', 'gpt4', 'llm', 'openai'] | 2024-01-09 | [('shishirpatil/gorilla', 0.6682367324829102, 'llm', 2), ('run-llama/rags', 0.644103467464447, 'llm', 4), ('farizrahman4u/loopgpt', 0.6415730118751526, 'llm', 2), ('chainlit/chainlit', 0.6109486222267151, 'llm', 3), ('openai/openai-cookbook', 0.6022109985351562, 'ml', 3), ('h2oai/h2o-llmstudio', 0.5947935581207275, 'llm', 3), ('xtekky/gpt4free', 0.5910773277282715, 'llm', 6), ('microsoft/promptflow', 0.5893070101737976, 'llm', 2), ('nomic-ai/gpt4all', 0.5768630504608154, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5764015913009644, 'perf', 1), ('deep-diver/llm-as-chatbot', 0.5747789144515991, 'llm', 1), ('microsoft/promptcraft-robotics', 0.5717716217041016, 'sim', 2), ('opengenerativeai/genossgpt', 0.56969153881073, 'llm', 2), ('pathwaycom/llm-app', 0.5610566735267639, 'llm', 2), ('microsoft/autogen', 0.5563012361526489, 'llm', 2), ('embedchain/embedchain', 0.5488071441650391, 'llm', 2), ('hwchase17/langchain', 0.5374903082847595, 'llm', 1), ('berriai/litellm', 0.5316495299339294, 'llm', 2), ('microsoft/semantic-kernel', 0.526870608329773, 'llm', 2), ('deepset-ai/haystack', 0.525952935218811, 'llm', 2), ('mnotgod96/appagent', 0.5122302174568176, 'llm', 3), ('alpha-vllm/llama2-accessory', 0.5011169910430908, 'llm', 0)] | 25 | 3 | null | 19.67 | 7 | 7 | 14 | 0 | 80 | 79 | 80 | 7 | 19 | 90 | 2.7 | 63 |
1,199 | llm | https://github.com/h2oai/h2o-llmstudio | [] | null | [] | [] | null | null | null | h2oai/h2o-llmstudio | h2o-llmstudio | 3,215 | 347 | 45 | Python | https://gpt-gm.h2o.ai | H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/ | h2oai | 2024-01-13 | 2023-04-17 | 41 | 78.142361 | https://avatars.githubusercontent.com/u/1402695?v=4 | H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/ | ['ai', 'chatbot', 'chatgpt', 'fine-tuning', 'finetuning', 'generative', 'generative-ai', 'gpt', 'llama', 'llama2', 'llm', 'llm-training'] | ['ai', 'chatbot', 'chatgpt', 'fine-tuning', 'finetuning', 'generative', 'generative-ai', 'gpt', 'llama', 'llama2', 'llm', 'llm-training'] | 2023-12-22 | [('hiyouga/llama-efficient-tuning', 0.6901037096977234, 'llm', 5), ('hiyouga/llama-factory', 0.6901035308837891, 'llm', 5), ('alpha-vllm/llama2-accessory', 0.6861495971679688, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6861023902893066, 'perf', 1), ('microsoft/promptflow', 0.6735444664955139, 'llm', 4), ('bentoml/openllm', 0.6586171388626099, 'ml-ops', 5), ('tigerlab-ai/tiger', 0.6549601554870605, 'llm', 3), ('pathwaycom/llm-app', 0.6417025327682495, 'llm', 2), ('nomic-ai/gpt4all', 0.6245695948600769, 'llm', 1), ('bigscience-workshop/petals', 0.6163656115531921, 'data', 4), ('deepset-ai/haystack', 0.6111219525337219, 'llm', 3), ('ludwig-ai/ludwig', 0.6097002625465393, 'ml-ops', 5), ('microsoft/semantic-kernel', 0.6094576716423035, 'llm', 2), ('agenta-ai/agenta', 0.6011561751365662, 'llm', 1), ('young-geng/easylm', 0.6009706258773804, 'llm', 2), ('mmabrouk/chatgpt-wrapper', 0.5947935581207275, 'llm', 3), ('iryna-kondr/scikit-llm', 0.5840808749198914, 'llm', 2), ('hwchase17/langchain', 0.5801489949226379, 'llm', 1), ('argilla-io/argilla', 0.5786020159721375, 'nlp', 2), ('confident-ai/deepeval', 0.5734099745750427, 'testing', 2), ('deep-diver/llm-as-chatbot', 0.5731402635574341, 'llm', 1), ('salesforce/codet5', 0.5726329684257507, 'nlp', 0), ('haotian-liu/llava', 0.5654820203781128, 'llm', 4), ('ray-project/llm-applications', 0.5635949373245239, 'llm', 2), ('predibase/lorax', 0.5625096559524536, 'llm', 4), ('bobazooba/xllm', 0.5602803230285645, 'llm', 5), ('microsoft/torchscale', 0.5583703517913818, 'llm', 0), ('embedchain/embedchain', 0.5581331253051758, 'llm', 3), ('shishirpatil/gorilla', 0.5525274872779846, 'llm', 2), ('microsoft/autogen', 0.5479278564453125, 'llm', 3), ('vllm-project/vllm', 0.5451328754425049, 'llm', 3), ('cheshire-cat-ai/core', 0.5447829365730286, 'llm', 3), ('lightning-ai/lit-gpt', 0.5436835289001465, 'llm', 1), ('microsoft/promptcraft-robotics', 0.5414144992828369, 'sim', 2), ('zilliztech/gptcache', 0.5407289266586304, 'llm', 5), ('lastmile-ai/aiconfig', 0.5382325053215027, 'util', 3), ('chainlit/chainlit', 0.5345412492752075, 'llm', 2), ('zrrskywalker/llama-adapter', 0.5344659686088562, 'llm', 1), ('hegelai/prompttools', 0.5304824709892273, 'llm', 0), ('eugeneyan/open-llms', 0.5287415385246277, 'study', 1), ('nebuly-ai/nebullvm', 0.5265906453132629, 'perf', 2), ('jerryjliu/llama_index', 0.5202019214630127, 'llm', 3), ('mnotgod96/appagent', 0.5174366235733032, 'llm', 3), ('run-llama/rags', 0.5137847065925598, 'llm', 3), ('citadel-ai/langcheck', 0.5101147890090942, 'llm', 0), ('dylanhogg/llmgraph', 0.5098133087158203, 'ml', 3), ('chatarena/chatarena', 0.5097920894622803, 'llm', 2), ('microsoft/lmops', 0.5096468329429626, 'llm', 2), ('next-gpt/next-gpt', 0.5090202689170837, 'llm', 2), ('lightning-ai/lit-llama', 0.5055845975875854, 'llm', 1), ('mlc-ai/web-llm', 0.5051769614219666, 'llm', 2), ('run-llama/llama-lab', 0.5041861534118652, 'llm', 1), ('eth-sri/lmql', 0.5039780139923096, 'llm', 1), ('alphasecio/langchain-examples', 0.5006608366966248, 'llm', 1)] | 24 | 5 | null | 5.33 | 133 | 102 | 9 | 1 | 15 | 20 | 15 | 133 | 119 | 90 | 0.9 | 63 |
729 | diffusion | https://github.com/compvis/stable-diffusion | ['diffusion', 'image-generation'] | null | [] | [] | null | null | null | compvis/stable-diffusion | stable-diffusion | 62,816 | 9,600 | 543 | Jupyter Notebook | https://ommer-lab.com/research/latent-diffusion-models/ | A latent text-to-image diffusion model | compvis | 2024-01-14 | 2022-08-10 | 76 | 817.30855 | https://avatars.githubusercontent.com/u/30233788?v=4 | A latent text-to-image diffusion model | [] | ['diffusion', 'image-generation'] | 2022-11-16 | [('sharonzhou/long_stable_diffusion', 0.6926607489585876, 'diffusion', 0), ('openai/glide-text2im', 0.6833638548851013, 'diffusion', 0), ('compvis/latent-diffusion', 0.655044674873352, 'diffusion', 2), ('stability-ai/stablediffusion', 0.6550443768501282, 'diffusion', 2), ('saharmor/dalle-playground', 0.6419358253479004, 'diffusion', 0), ('nateraw/stable-diffusion-videos', 0.6355494856834412, 'diffusion', 0), ('huggingface/diffusers', 0.629136860370636, 'diffusion', 2), ('albarji/mixture-of-diffusers', 0.5530049204826355, 'diffusion', 0), ('jina-ai/discoart', 0.5315988659858704, 'diffusion', 1), ('automatic1111/stable-diffusion-webui', 0.5289968252182007, 'diffusion', 2), ('openai/clip', 0.5251467227935791, 'ml-dl', 0)] | 8 | 1 | null | 0 | 58 | 10 | 17 | 14 | 0 | 0 | 0 | 58 | 105 | 90 | 1.8 | 62 |
244 | ml | https://github.com/tencentarc/gfpgan | [] | null | [] | [] | null | null | null | tencentarc/gfpgan | GFPGAN | 33,415 | 5,481 | 481 | Python | null | GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. | tencentarc | 2024-01-14 | 2021-03-19 | 149 | 223.404967 | https://avatars.githubusercontent.com/u/83739826?v=4 | GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. | ['deep-learning', 'face-restoration', 'gan', 'gfpgan', 'image-restoration', 'pytorch', 'super-resolution'] | ['deep-learning', 'face-restoration', 'gan', 'gfpgan', 'image-restoration', 'pytorch', 'super-resolution'] | 2022-09-16 | [('xpixelgroup/basicsr', 0.6321846842765808, 'ml-dl', 2), ('xinntao/real-esrgan', 0.5772732496261597, 'ml-dl', 3), ('deepfakes/faceswap', 0.5402413606643677, 'ml-dl', 1), ('mchong6/jojogan', 0.5290706753730774, 'data', 0)] | 11 | 3 | null | 0 | 45 | 4 | 34 | 16 | 0 | 5 | 5 | 45 | 31 | 90 | 0.7 | 62 |
232 | template | https://github.com/cookiecutter/cookiecutter | [] | null | [] | [] | null | null | null | cookiecutter/cookiecutter | cookiecutter | 20,987 | 1,986 | 227 | Python | https://pypi.org/project/cookiecutter/ | A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects. | cookiecutter | 2024-01-14 | 2013-07-14 | 550 | 38.13837 | https://avatars.githubusercontent.com/u/12502901?v=4 | A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects. | ['cookiecutter'] | ['cookiecutter'] | 2023-11-27 | [('lyz-code/cookiecutter-python-project', 0.8542928099632263, 'template', 1), ('tedivm/robs_awesome_python_template', 0.8344708681106567, 'template', 0), ('giswqs/pypackage', 0.7356756329536438, 'template', 1), ('ionelmc/cookiecutter-pylibrary', 0.7163523435592651, 'template', 1), ('buuntu/fastapi-react', 0.6335521340370178, 'template', 1), ('crmne/cookiecutter-modern-datascience', 0.5783246755599976, 'template', 1), ('tezromach/python-package-template', 0.5202876925468445, 'template', 1), ('pypa/hatch', 0.5061737895011902, 'util', 0)] | 318 | 6 | null | 1.56 | 90 | 43 | 128 | 2 | 7 | 4 | 7 | 90 | 105 | 90 | 1.2 | 62 |
1,055 | study | https://github.com/microsoft/recommenders | [] | null | [] | [] | null | null | null | microsoft/recommenders | recommenders | 17,261 | 2,965 | 270 | Python | https://microsoft-recommenders.readthedocs.io/en/latest/ | Best Practices on Recommendation Systems | microsoft | 2024-01-14 | 2018-09-19 | 279 | 61.677897 | https://avatars.githubusercontent.com/u/142452264?v=4 | Best Practices on Recommendation Systems | ['artificial-intelligence', 'azure', 'data-science', 'deep-learning', 'jupyter-notebook', 'kubernetes', 'machine-learning', 'microsoft', 'operationalization', 'ranking', 'rating', 'recommendation', 'recommendation-algorithm', 'recommendation-engine', 'recommendation-system', 'recommender', 'tutorial'] | ['artificial-intelligence', 'azure', 'data-science', 'deep-learning', 'jupyter-notebook', 'kubernetes', 'machine-learning', 'microsoft', 'operationalization', 'ranking', 'rating', 'recommendation', 'recommendation-algorithm', 'recommendation-engine', 'recommendation-system', 'recommender', 'tutorial'] | 2023-12-23 | [('rucaibox/recbole', 0.5956623554229736, 'ml', 3), ('nicolashug/surprise', 0.5881096720695496, 'ml', 3), ('pytorch/torchrec', 0.5602710247039795, 'ml-dl', 2), ('jacopotagliabue/reclist', 0.5187485218048096, 'ml', 1)] | 128 | 2 | null | 6.81 | 52 | 27 | 65 | 1 | 0 | 2 | 2 | 52 | 79 | 90 | 1.5 | 62 |
41 | util | https://github.com/kivy/kivy | [] | null | [] | [] | null | null | null | kivy/kivy | kivy | 16,614 | 3,096 | 606 | Python | https://kivy.org | Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS | kivy | 2024-01-14 | 2010-11-03 | 690 | 24.048387 | https://avatars.githubusercontent.com/u/1266152?v=4 | Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS | ['android', 'app', 'ios', 'kivy', 'linux', 'macos', 'ui', 'windows'] | ['android', 'app', 'ios', 'kivy', 'linux', 'macos', 'ui', 'windows'] | 2024-01-05 | [('beeware/toga', 0.692936360836029, 'gui', 0), ('r0x0r/pywebview', 0.6854493618011475, 'gui', 2), ('willmcgugan/textual', 0.632539689540863, 'term', 0), ('hoffstadt/dearpygui', 0.6317042112350464, 'gui', 4), ('flet-dev/flet', 0.6066066026687622, 'web', 2), ('pysimplegui/pysimplegui', 0.600288450717926, 'gui', 0), ('alphasecio/langchain-examples', 0.5670594573020935, 'llm', 0), ('wxwidgets/phoenix', 0.5668678879737854, 'gui', 2), ('dddomodossola/remi', 0.5648102164268494, 'gui', 1), ('urwid/urwid', 0.5640290975570679, 'term', 0), ('openai/openai-python', 0.5627065300941467, 'util', 0), ('parthjadhav/tkinter-designer', 0.554401695728302, 'gui', 0), ('vitalik/django-ninja', 0.5482510328292847, 'web', 0), ('pypy/pypy', 0.540271520614624, 'util', 0), ('gradio-app/gradio', 0.5393166542053223, 'viz', 1), ('pyglet/pyglet', 0.5390869975090027, 'gamedev', 0), ('pallets/flask', 0.535079836845398, 'web', 0), ('reflex-dev/reflex', 0.5318344831466675, 'web', 0), ('holoviz/panel', 0.5100237131118774, 'viz', 0), ('panda3d/panda3d', 0.5057852268218994, 'gamedev', 0), ('masoniteframework/masonite', 0.5023773312568665, 'web', 0), ('fastai/ghapi', 0.5002898573875427, 'util', 0)] | 604 | 6 | null | 3.19 | 827 | 437 | 161 | 1 | 3 | 4 | 3 | 827 | 1,087 | 90 | 1.3 | 62 |
314 | gui | https://github.com/hoffstadt/dearpygui | [] | null | [] | [] | null | null | null | hoffstadt/dearpygui | DearPyGui | 11,691 | 639 | 150 | C++ | https://dearpygui.readthedocs.io/en/latest/ | Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies | hoffstadt | 2024-01-14 | 2020-05-28 | 191 | 60.981371 | null | Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies | ['cpp', 'cross-platform', 'dearpygui', 'graphics', 'gui', 'imgui', 'linux', 'macos', 'native', 'python-gui', 'toolkit', 'tools', 'ui', 'windows'] | ['cpp', 'cross-platform', 'dearpygui', 'graphics', 'gui', 'imgui', 'linux', 'macos', 'native', 'python-gui', 'toolkit', 'tools', 'ui', 'windows'] | 2024-01-11 | [('beeware/toga', 0.7974780201911926, 'gui', 2), ('parthjadhav/tkinter-designer', 0.6940200924873352, 'gui', 1), ('pysimplegui/pysimplegui', 0.6711195111274719, 'gui', 2), ('pypy/pypy', 0.6707800030708313, 'util', 0), ('urwid/urwid', 0.6700049042701721, 'term', 0), ('r0x0r/pywebview', 0.6651965379714966, 'gui', 3), ('pyglet/pyglet', 0.6631710529327393, 'gamedev', 0), ('willmcgugan/textual', 0.6536368131637573, 'term', 0), ('wxwidgets/phoenix', 0.6336509585380554, 'gui', 4), ('kivy/kivy', 0.6317042112350464, 'util', 4), ('pyston/pyston', 0.6223757863044739, 'util', 0), ('jquast/blessed', 0.6031554937362671, 'term', 0), ('python/cpython', 0.6008025407791138, 'util', 0), ('dddomodossola/remi', 0.5960089564323425, 'gui', 2), ('holoviz/panel', 0.5953347086906433, 'viz', 1), ('alexmojaki/snoop', 0.5897102952003479, 'debug', 0), ('pytoolz/toolz', 0.5808964371681213, 'util', 0), ('eleutherai/pyfra', 0.5808343887329102, 'ml', 0), ('google/python-fire', 0.5763037800788879, 'term', 0), ('webpy/webpy', 0.5751984119415283, 'web', 0), ('fastai/fastcore', 0.5673369765281677, 'util', 0), ('pyscript/pyscript-cli', 0.5643460750579834, 'web', 0), ('holoviz/holoviz', 0.5614981651306152, 'viz', 0), ('huggingface/huggingface_hub', 0.5539893507957458, 'ml', 0), ('pallets/click', 0.5539004802703857, 'term', 0), ('pdm-project/pdm', 0.5533838868141174, 'util', 0), ('secdev/scapy', 0.5505430698394775, 'util', 0), ('pexpect/pexpect', 0.5491853952407837, 'util', 0), ('pypa/hatch', 0.5478973388671875, 'util', 0), ('ethereum/web3.py', 0.5474371314048767, 'crypto', 0), ('minimaxir/simpleaichat', 0.5460814237594604, 'llm', 0), ('cython/cython', 0.5458163619041443, 'util', 1), ('libtcod/python-tcod', 0.5448720455169678, 'gamedev', 0), ('masoniteframework/masonite', 0.5427703261375427, 'web', 0), ('faster-cpython/tools', 0.5421075820922852, 'perf', 0), ('pympler/pympler', 0.5417070388793945, 'perf', 0), ('bottlepy/bottle', 0.541211724281311, 'web', 0), ('tqdm/tqdm', 0.5399507284164429, 'term', 1), ('erotemic/ubelt', 0.5396130681037903, 'util', 1), ('landscapeio/prospector', 0.5395547747612, 'util', 0), ('tmbo/questionary', 0.5394479632377625, 'term', 0), ('klen/muffin', 0.5390740036964417, 'web', 0), ('micropython/micropython', 0.5389625430107117, 'util', 0), ('bokeh/bokeh', 0.5377543568611145, 'viz', 0), ('hhatto/autopep8', 0.5373272895812988, 'util', 0), ('gradio-app/gradio', 0.5356285572052002, 'viz', 1), ('plotly/plotly.py', 0.5339773297309875, 'viz', 0), ('dylanhogg/awesome-python', 0.5330666899681091, 'study', 0), ('grantjenks/blue', 0.5329349040985107, 'util', 0), ('pygments/pygments', 0.5314857959747314, 'util', 0), ('google/gin-config', 0.5313805341720581, 'util', 0), ('psf/black', 0.5271217226982117, 'util', 0), ('pyodide/micropip', 0.5266197919845581, 'util', 0), ('indygreg/pyoxidizer', 0.5257773995399475, 'util', 0), ('jiffyclub/snakeviz', 0.5256134867668152, 'profiling', 0), ('imageio/imageio', 0.5239776968955994, 'util', 0), ('pygame/pygame', 0.5225834846496582, 'gamedev', 0), ('pyinfra-dev/pyinfra', 0.5215190649032593, 'util', 0), ('faster-cpython/ideas', 0.5212865471839905, 'perf', 0), ('pygamelib/pygamelib', 0.5179816484451294, 'gamedev', 0), ('sqlalchemy/mako', 0.5178695917129517, 'template', 0), ('pallets/flask', 0.5168485045433044, 'web', 0), ('exaloop/codon', 0.5152654647827148, 'perf', 0), ('rstudio/py-shiny', 0.5147618651390076, 'web', 0), ('pypa/virtualenv', 0.5124236941337585, 'util', 0), ('renpy/renpy', 0.5120179057121277, 'viz', 0), ('adafruit/circuitpython', 0.511806309223175, 'util', 0), ('flet-dev/flet', 0.5117893815040588, 'web', 0), ('klen/py-frameworks-bench', 0.511713981628418, 'perf', 0), ('pyodide/pyodide', 0.5109636187553406, 'util', 0), ('ipython/ipyparallel', 0.5102288126945496, 'perf', 0), ('allrod5/injectable', 0.508715033531189, 'util', 0), ('plotly/dash', 0.5085344314575195, 'viz', 0), ('goldmansachs/gs-quant', 0.5079163908958435, 'finance', 0), ('beeware/briefcase', 0.5077422261238098, 'util', 0), ('pyqtgraph/pyqtgraph', 0.5063014626502991, 'viz', 0), ('tkrabel/bamboolib', 0.5062575936317444, 'pandas', 0), ('xonsh/xonsh', 0.504555881023407, 'util', 0), ('timofurrer/awesome-asyncio', 0.5044320225715637, 'study', 0), ('python-poetry/cleo', 0.5041629672050476, 'term', 0), ('python-poetry/poetry', 0.5035780668258667, 'util', 0), ('microsoft/playwright-python', 0.5034270882606506, 'testing', 0), ('asweigart/pyperclip', 0.5023604035377502, 'util', 0), ('py4j/py4j', 0.5022397041320801, 'util', 0), ('scrapy/scrapy', 0.5022242069244385, 'data', 0), ('1200wd/bitcoinlib', 0.5015420913696289, 'crypto', 0), ('intel/intel-extension-for-pytorch', 0.5012747645378113, 'perf', 0), ('requests/toolbelt', 0.5012592077255249, 'util', 0), ('willmcgugan/rich', 0.5006871223449707, 'term', 0), ('gaogaotiantian/viztracer', 0.5000486373901367, 'profiling', 0)] | 65 | 3 | null | 1.02 | 88 | 48 | 44 | 0 | 3 | 7 | 3 | 88 | 139 | 90 | 1.6 | 62 |
989 | finance | https://github.com/ranaroussi/yfinance | [] | null | [] | ['yfinance'] | 1 | null | null | ranaroussi/yfinance | yfinance | 11,035 | 2,104 | 235 | Python | https://aroussi.com/post/python-yahoo-finance | Download market data from Yahoo! Finance's API | ranaroussi | 2024-01-14 | 2017-05-21 | 349 | 31.593047 | null | Download market data from Yahoo! Finance's API | ['financial-data', 'fix-yahoo-finance', 'market-data', 'pandas', 'stock-data', 'yahoo-finance', 'yahoo-finance-api'] | ['financial-data', 'fix-yahoo-finance', 'market-data', 'pandas', 'stock-data', 'yahoo-finance', 'yahoo-finance-api'] | 2024-01-11 | [('cuemacro/findatapy', 0.6290664672851562, 'finance', 1), ('pydata/pandas-datareader', 0.6126816868782043, 'pandas', 3), ('hydrosquall/tiingo-python', 0.5750361084938049, 'finance', 0), ('matplotlib/mplfinance', 0.5448886156082153, 'finance', 1), ('mega-barrel/yfin-etl', 0.535876452922821, 'finance', 1), ('stefmolin/stock-analysis', 0.5187216401100159, 'finance', 1)] | 102 | 1 | null | 4.56 | 142 | 94 | 81 | 0 | 37 | 13 | 37 | 142 | 547 | 90 | 3.9 | 62 |
639 | util | https://github.com/pyinstaller/pyinstaller | [] | null | [] | [] | null | null | null | pyinstaller/pyinstaller | pyinstaller | 10,966 | 1,970 | 232 | Python | http://www.pyinstaller.org | Freeze (package) Python programs into stand-alone executables | pyinstaller | 2024-01-14 | 2011-11-23 | 635 | 17.246012 | https://avatars.githubusercontent.com/u/1215332?v=4 | Freeze (package) Python programs into stand-alone executables | ['bundle', 'package', 'py2app', 'py2exe', 'pyinstaller', 'python-to-exe'] | ['bundle', 'package', 'py2app', 'py2exe', 'pyinstaller', 'python-to-exe'] | 2024-01-13 | [('beeware/briefcase', 0.6962027549743652, 'util', 3), ('ofek/pyapp', 0.5914837121963501, 'util', 1), ('indygreg/pyoxidizer', 0.5304632782936096, 'util', 0), ('pyodide/micropip', 0.5264869332313538, 'util', 0), ('pypa/pipx', 0.5007230639457703, 'util', 0)] | 461 | 4 | null | 8.67 | 312 | 280 | 148 | 0 | 13 | 6 | 13 | 312 | 563 | 90 | 1.8 | 62 |
1,776 | ml | https://github.com/neonbjb/tortoise-tts | ['text-to-speech', 'voice'] | null | [] | [] | null | null | null | neonbjb/tortoise-tts | tortoise-tts | 10,615 | 1,544 | 159 | Jupyter Notebook | null | A multi-voice TTS system trained with an emphasis on quality | neonbjb | 2024-01-14 | 2022-01-28 | 104 | 101.509563 | null | A multi-voice TTS system trained with an emphasis on quality | [] | ['text-to-speech', 'voice'] | 2023-11-22 | [('plachtaa/vall-e-x', 0.6283189058303833, 'llm', 1), ('myshell-ai/openvoice', 0.57065349817276, 'nlp', 1), ('m-bain/whisperx', 0.5033969283103943, 'nlp', 0)] | 34 | 4 | null | 1.75 | 118 | 42 | 24 | 2 | 0 | 2 | 2 | 118 | 151 | 90 | 1.3 | 62 |
1,334 | ml | https://github.com/facebookresearch/animateddrawings | ['animation'] | null | [] | [] | null | null | null | facebookresearch/animateddrawings | AnimatedDrawings | 9,893 | 837 | 84 | Python | null | Code to accompany "A Method for Animating Children's Drawings of the Human Figure" | facebookresearch | 2024-01-14 | 2022-11-30 | 60 | 162.561033 | https://avatars.githubusercontent.com/u/16943930?v=4 | Code to accompany "A Method for Animating Children's Drawings of the Human Figure" | [] | ['animation'] | 2023-12-10 | [] | 14 | 2 | null | 1.56 | 35 | 24 | 14 | 1 | 1 | 1 | 1 | 35 | 55 | 90 | 1.6 | 62 |
126 | perf | https://github.com/modin-project/modin | [] | null | [] | [] | 1 | null | null | modin-project/modin | modin | 9,219 | 631 | 116 | Python | http://modin.readthedocs.io | Modin: Scale your Pandas workflows by changing a single line of code | modin-project | 2024-01-14 | 2018-06-21 | 292 | 31.494876 | https://avatars.githubusercontent.com/u/40475955?v=4 | Modin: Scale your Pandas workflows by changing a single line of code | ['analytics', 'data-science', 'dataframe', 'datascience', 'distributed', 'modin', 'pandas', 'sql'] | ['analytics', 'data-science', 'dataframe', 'datascience', 'distributed', 'modin', 'pandas', 'sql'] | 2024-01-13 | [('jmcarpenter2/swifter', 0.6068665385246277, 'pandas', 2), ('nalepae/pandarallel', 0.6011874675750732, 'pandas', 1), ('lux-org/lux', 0.5601602792739868, 'viz', 2), ('ydataai/ydata-profiling', 0.5375041365623474, 'pandas', 2), ('kestra-io/kestra', 0.5311633348464966, 'ml-ops', 0), ('hi-primus/optimus', 0.5256850123405457, 'ml-ops', 1), ('flyteorg/flyte', 0.5223826169967651, 'ml-ops', 1), ('adamerose/pandasgui', 0.5174034237861633, 'pandas', 2), ('pytables/pytables', 0.5136765837669373, 'data', 0), ('tkrabel/bamboolib', 0.5066853761672974, 'pandas', 1)] | 124 | 3 | null | 10.35 | 332 | 274 | 68 | 0 | 19 | 15 | 19 | 331 | 319 | 90 | 1 | 62 |
438 | ml-dl | https://github.com/kornia/kornia | [] | null | [] | [] | null | null | null | kornia/kornia | kornia | 9,004 | 916 | 127 | Python | https://kornia.readthedocs.io | Geometric Computer Vision Library for SpatialAI | kornia | 2024-01-14 | 2018-08-22 | 283 | 31.720181 | https://avatars.githubusercontent.com/u/56968752?v=4 | Geometric Computer Vision Library for SpatialAI | ['artificial-intelligence', 'computer-vision', 'deep-learning', 'image-processing', 'machine-learning', 'neural-network', 'pytorch', 'robotics', 'spatial-ai'] | ['artificial-intelligence', 'computer-vision', 'deep-learning', 'image-processing', 'machine-learning', 'neural-network', 'pytorch', 'robotics', 'spatial-ai'] | 2024-01-13 | [('deci-ai/super-gradients', 0.6162040829658508, 'ml-dl', 4), ('isl-org/open3d', 0.6128343939781189, 'sim', 2), ('pyg-team/pytorch_geometric', 0.5945971012115479, 'ml-dl', 2), ('roboflow/supervision', 0.5887291431427002, 'ml', 5), ('microsoft/torchgeo', 0.5526466369628906, 'gis', 3), ('pytorch/rl', 0.5435752272605896, 'ml-rl', 3), ('earthlab/earthpy', 0.5408483743667603, 'gis', 0), ('lightly-ai/lightly', 0.5407032370567322, 'ml', 4), ('tensorlayer/tensorlayer', 0.5397638082504272, 'ml-rl', 3), ('nvlabs/gcvit', 0.5384776592254639, 'diffusion', 1), ('scikit-geometry/scikit-geometry', 0.5317684412002563, 'gis', 0), ('geomstats/geomstats', 0.5275140404701233, 'math', 2), ('azavea/raster-vision', 0.5268778204917908, 'gis', 4), ('roboflow/notebooks', 0.5266382098197937, 'study', 4), ('lucidrains/imagen-pytorch', 0.5201680064201355, 'ml-dl', 2), ('activeloopai/deeplake', 0.516307532787323, 'ml-ops', 5), ('kevinmusgrave/pytorch-metric-learning', 0.5158526301383972, 'ml', 4), ('remotesensinglab/raster4ml', 0.5086722373962402, 'gis', 1), ('facebookresearch/pytorch3d', 0.5057213306427002, 'ml-dl', 0), ('facebookresearch/habitat-lab', 0.502574622631073, 'sim', 3), ('pytorch/ignite', 0.5025068521499634, 'ml-dl', 4), ('albumentations-team/albumentations', 0.5021526217460632, 'ml-dl', 3)] | 245 | 6 | null | 6.13 | 143 | 95 | 66 | 0 | 5 | 8 | 5 | 144 | 110 | 90 | 0.8 | 62 |
129 | viz | https://github.com/altair-viz/altair | ['visualization'] | null | [] | [] | null | null | null | altair-viz/altair | altair | 8,655 | 785 | 141 | Python | https://altair-viz.github.io/ | Declarative statistical visualization library for Python | altair-viz | 2024-01-13 | 2015-09-19 | 436 | 19.831424 | https://avatars.githubusercontent.com/u/22396732?v=4 | Declarative statistical visualization library for Python | [] | ['visualization'] | 2024-01-09 | [('mwaskom/seaborn', 0.8215170502662659, 'viz', 0), ('enthought/mayavi', 0.7132139801979065, 'viz', 1), ('holoviz/holoviz', 0.7110622525215149, 'viz', 0), ('has2k1/plotnine', 0.6832043528556824, 'viz', 0), ('residentmario/geoplot', 0.6802260875701904, 'gis', 0), ('alexmojaki/heartrate', 0.6655700206756592, 'debug', 1), ('pyqtgraph/pyqtgraph', 0.6555560827255249, 'viz', 1), ('man-group/dtale', 0.6516591310501099, 'viz', 1), ('holoviz/geoviews', 0.6453191041946411, 'gis', 0), ('matplotlib/matplotlib', 0.6370353102684021, 'viz', 0), ('bokeh/bokeh', 0.6335301399230957, 'viz', 1), ('scitools/iris', 0.6287659406661987, 'gis', 0), ('contextlab/hypertools', 0.6141685843467712, 'ml', 1), ('plotly/plotly.py', 0.6128622889518738, 'viz', 1), ('scitools/cartopy', 0.6086525917053223, 'gis', 0), ('holoviz/hvplot', 0.5933358669281006, 'pandas', 0), ('kanaries/pygwalker', 0.5906645655632019, 'pandas', 1), ('gaogaotiantian/viztracer', 0.5886167287826538, 'profiling', 1), ('holoviz/panel', 0.5875522494316101, 'viz', 0), ('dfki-ric/pytransform3d', 0.5856305360794067, 'math', 1), ('westhealth/pyvis', 0.5836617946624756, 'graph', 0), ('pysal/pysal', 0.5805773735046387, 'gis', 0), ('vispy/vispy', 0.5802785158157349, 'viz', 1), ('pandas-dev/pandas', 0.5787591338157654, 'pandas', 0), ('gregorhd/mapcompare', 0.5779780149459839, 'gis', 0), ('wesm/pydata-book', 0.5764631032943726, 'study', 0), ('giswqs/geemap', 0.5686102509498596, 'gis', 0), ('nschloe/perfplot', 0.5681192278862, 'perf', 0), ('graphistry/pygraphistry', 0.5656019449234009, 'data', 1), ('jakevdp/pythondatasciencehandbook', 0.5655259490013123, 'study', 0), ('pyglet/pyglet', 0.5653769969940186, 'gamedev', 0), ('eleutherai/pyfra', 0.5628342032432556, 'ml', 0), ('artelys/geonetworkx', 0.5582142472267151, 'gis', 0), ('datapane/datapane', 0.556462287902832, 'viz', 0), ('marcomusy/vedo', 0.5546357035636902, 'viz', 1), ('brandtbucher/specialist', 0.5505017042160034, 'perf', 0), ('cuemacro/chartpy', 0.5500401258468628, 'viz', 0), ('vizzuhq/ipyvizzu', 0.5488370656967163, 'jupyter', 0), ('opengeos/leafmap', 0.5457186698913574, 'gis', 0), ('lux-org/lux', 0.5405464172363281, 'viz', 1), ('imageio/imageio', 0.5385008454322815, 'util', 0), ('csurfer/pyheat', 0.5379376411437988, 'profiling', 0), ('albahnsen/pycircular', 0.5373349189758301, 'math', 0), ('gboeing/pynamical', 0.5344410538673401, 'sim', 1), ('nomic-ai/deepscatter', 0.5337156653404236, 'viz', 1), ('connorferster/handcalcs', 0.531620442867279, 'jupyter', 0), ('numpy/numpy', 0.5299937129020691, 'math', 0), ('pyutils/line_profiler', 0.5267626643180847, 'profiling', 0), ('python/cpython', 0.526507556438446, 'util', 0), ('earthlab/earthpy', 0.5252060294151306, 'gis', 0), ('makepath/xarray-spatial', 0.5251989364624023, 'gis', 0), ('pyston/pyston', 0.5246127843856812, 'util', 0), ('raphaelquast/eomaps', 0.5242673754692078, 'gis', 1), ('pytoolz/toolz', 0.5240060687065125, 'util', 0), ('maartenbreddels/ipyvolume', 0.5231117010116577, 'jupyter', 0), ('mckinsey/vizro', 0.5226520895957947, 'viz', 1), ('rasbt/mlxtend', 0.5204195976257324, 'ml', 0), ('rjt1990/pyflux', 0.5199966430664062, 'time-series', 0), ('holoviz/datashader', 0.5193212032318115, 'gis', 0), ('holoviz/holoviews', 0.5143608450889587, 'viz', 0), ('bmabey/pyldavis', 0.5086315274238586, 'ml', 0), ('pygraphviz/pygraphviz', 0.5070845484733582, 'viz', 0), ('stan-dev/pystan', 0.506462574005127, 'ml', 0)] | 160 | 7 | null | 4.88 | 115 | 90 | 101 | 0 | 8 | 4 | 8 | 115 | 302 | 90 | 2.6 | 62 |
172 | ml-dl | https://github.com/facebookresearch/pytorch3d | [] | null | [] | [] | null | null | null | facebookresearch/pytorch3d | pytorch3d | 7,977 | 1,236 | 146 | Python | https://pytorch3d.org/ | PyTorch3D is FAIR's library of reusable components for deep learning with 3D data | facebookresearch | 2024-01-14 | 2019-10-25 | 222 | 35.84018 | https://avatars.githubusercontent.com/u/16943930?v=4 | PyTorch3D is FAIR's library of reusable components for deep learning with 3D data | [] | [] | 2024-01-04 | [('isl-org/open3d', 0.634926438331604, 'sim', 0), ('pytorch/ignite', 0.6142131686210632, 'ml-dl', 0), ('nicolas-chaulet/torch-points3d', 0.6138631701469421, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.5983558893203735, 'perf', 0), ('mrdbourke/pytorch-deep-learning', 0.5950154066085815, 'study', 0), ('pyg-team/pytorch_geometric', 0.5885642766952515, 'ml-dl', 0), ('skorch-dev/skorch', 0.5811278223991394, 'ml-dl', 0), ('xl0/lovely-tensors', 0.5774106383323669, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.574776828289032, 'study', 0), ('ashleve/lightning-hydra-template', 0.565503716468811, 'util', 0), ('arogozhnikov/einops', 0.5348989963531494, 'ml-dl', 0), ('pytorch/data', 0.5338151454925537, 'data', 0), ('cvxgrp/pymde', 0.5327015519142151, 'ml', 0), ('lightly-ai/lightly', 0.5310624241828918, 'ml', 0), ('tensorlayer/tensorlayer', 0.530800461769104, 'ml-rl', 0), ('denys88/rl_games', 0.5304609537124634, 'ml-rl', 0), ('google-research/deeplab2', 0.5299793481826782, 'ml', 0), ('nvidia/apex', 0.5290184020996094, 'ml-dl', 0), ('thu-ml/tianshou', 0.5248837471008301, 'ml-rl', 0), ('dmlc/dgl', 0.5240106582641602, 'ml-dl', 0), ('karpathy/micrograd', 0.5227355360984802, 'study', 0), ('huggingface/huggingface_hub', 0.5197669863700867, 'ml', 0), ('weecology/deepforest', 0.5166642069816589, 'gis', 0), ('horovod/horovod', 0.5143802165985107, 'ml-ops', 0), ('uber/petastorm', 0.5134731531143188, 'data', 0), ('nvlabs/gcvit', 0.5093544125556946, 'diffusion', 0), ('huggingface/transformers', 0.508711040019989, 'nlp', 0), ('pytorch/pytorch', 0.5076754093170166, 'ml-dl', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5057374238967896, 'study', 0), ('kornia/kornia', 0.5057213306427002, 'ml-dl', 0), ('pytorch/torchrec', 0.5049778819084167, 'ml-dl', 0), ('huggingface/datasets', 0.5045773386955261, 'nlp', 0), ('pytorch/rl', 0.5044132471084595, 'ml-rl', 0), ('mdbloice/augmentor', 0.5032729506492615, 'ml', 0), ('neuralmagic/deepsparse', 0.5011691451072693, 'nlp', 0)] | 133 | 5 | null | 2.08 | 95 | 66 | 51 | 0 | 3 | 4 | 3 | 95 | 215 | 90 | 2.3 | 62 |
548 | ml | https://github.com/open-mmlab/mmsegmentation | [] | null | [] | [] | null | null | null | open-mmlab/mmsegmentation | mmsegmentation | 6,943 | 2,405 | 54 | Python | https://mmsegmentation.readthedocs.io/en/latest/ | OpenMMLab Semantic Segmentation Toolbox and Benchmark. | open-mmlab | 2024-01-14 | 2020-06-14 | 189 | 36.68 | https://avatars.githubusercontent.com/u/10245193?v=4 | OpenMMLab Semantic Segmentation Toolbox and Benchmark. | ['deeplabv3', 'image-segmentation', 'medical-image-segmentation', 'pspnet', 'pytorch', 'realtime-segmentation', 'retinal-vessel-segmentation', 'semantic-segmentation', 'swin-transformer', 'transformer', 'vessel-segmentation'] | ['deeplabv3', 'image-segmentation', 'medical-image-segmentation', 'pspnet', 'pytorch', 'realtime-segmentation', 'retinal-vessel-segmentation', 'semantic-segmentation', 'swin-transformer', 'transformer', 'vessel-segmentation'] | 2023-12-14 | [('open-mmlab/mmdetection', 0.7892122864723206, 'ml', 3), ('open-mmlab/mmcv', 0.6504673361778259, 'ml', 0), ('roboflow/supervision', 0.6128215193748474, 'ml', 1), ('nvlabs/gcvit', 0.5941908359527588, 'diffusion', 1), ('deci-ai/super-gradients', 0.5933340787887573, 'ml-dl', 2), ('google-research/deeplab2', 0.5815913081169128, 'ml', 0), ('fepegar/torchio', 0.5752494931221008, 'ml-dl', 1), ('open-mmlab/mmediting', 0.5589426755905151, 'ml', 1), ('microsoft/swin-transformer', 0.5363519191741943, 'ml', 2), ('aleju/imgaug', 0.5349984169006348, 'ml', 0), ('rwightman/pytorch-image-models', 0.5257945656776428, 'ml-dl', 1), ('project-monai/monai', 0.5131828188896179, 'ml', 1), ('albumentations-team/albumentations', 0.5108982920646667, 'ml-dl', 1), ('lutzroeder/netron', 0.5060480237007141, 'ml', 1), ('huggingface/datasets', 0.5029417276382446, 'nlp', 1)] | 165 | 6 | null | 3.88 | 189 | 57 | 44 | 1 | 10 | 13 | 10 | 188 | 207 | 90 | 1.1 | 62 |
3 | ml | https://github.com/awslabs/autogluon | [] | null | [] | [] | null | null | null | awslabs/autogluon | autogluon | 6,696 | 816 | 100 | Python | https://auto.gluon.ai/ | AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data | awslabs | 2024-01-14 | 2019-07-29 | 235 | 28.476306 | https://avatars.githubusercontent.com/u/92389699?v=4 | AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data | ['autogluon', 'automated-machine-learning', 'automl', 'computer-vision', 'data-science', 'deep-learning', 'ensemble-learning', 'forecasting', 'gluon', 'hyperparameter-optimization', 'image-classification', 'machine-learning', 'natural-language-processing', 'object-detection', 'pytorch', 'scikit-learn', 'structured-data', 'tabular-data', 'time-series', 'transfer-learning'] | ['autogluon', 'automated-machine-learning', 'automl', 'computer-vision', 'data-science', 'deep-learning', 'ensemble-learning', 'forecasting', 'gluon', 'hyperparameter-optimization', 'image-classification', 'machine-learning', 'natural-language-processing', 'object-detection', 'pytorch', 'scikit-learn', 'structured-data', 'tabular-data', 'time-series', 'transfer-learning'] | 2024-01-08 | [('mljar/mljar-supervised', 0.7640585899353027, 'ml', 6), ('keras-team/autokeras', 0.7593497633934021, 'ml-dl', 4), ('winedarksea/autots', 0.7558371424674988, 'time-series', 5), ('microsoft/flaml', 0.7324180603027344, 'ml', 9), ('microsoft/nni', 0.7000966668128967, 'ml', 7), ('automl/auto-sklearn', 0.672629177570343, 'ml', 4), ('huggingface/autotrain-advanced', 0.6629055142402649, 'ml', 3), ('nccr-itmo/fedot', 0.6268003582954407, 'ml-ops', 4), ('ourownstory/neural_prophet', 0.6234149932861328, 'ml', 5), ('ydataai/ydata-synthetic', 0.5872030258178711, 'data', 4), ('alpa-projects/alpa', 0.5790343284606934, 'ml-dl', 2), ('sktime/sktime', 0.5768527984619141, 'time-series', 5), ('huggingface/datasets', 0.5675216913223267, 'nlp', 5), ('salesforce/merlion', 0.5632773637771606, 'time-series', 5), ('sdv-dev/sdv', 0.562446117401123, 'data', 3), ('mosaicml/composer', 0.554071307182312, 'ml-dl', 3), ('torantulino/auto-gpt', 0.5540371537208557, 'llm', 0), ('aleju/imgaug', 0.5523484349250793, 'ml', 2), ('featurelabs/featuretools', 0.5521774291992188, 'ml', 5), ('milvus-io/bootcamp', 0.5507424473762512, 'data', 2), ('xplainable/xplainable', 0.5499810576438904, 'ml-interpretability', 2), ('towhee-io/towhee', 0.5480068325996399, 'ml-ops', 2), ('neuralmagic/sparseml', 0.5449380278587341, 'ml-dl', 5), ('open-mmlab/mmediting', 0.5436397194862366, 'ml', 3), ('shankarpandala/lazypredict', 0.5431965589523315, 'ml', 2), ('nixtla/statsforecast', 0.5410817265510559, 'time-series', 5), ('roboflow/supervision', 0.54073566198349, 'ml', 5), ('microsoft/torchgeo', 0.5401058197021484, 'gis', 3), ('activeloopai/deeplake', 0.5394940376281738, 'ml-ops', 5), ('lutzroeder/netron', 0.5327269434928894, 'ml', 3), ('epistasislab/tpot', 0.5319231748580933, 'ml', 6), ('firmai/atspy', 0.53136146068573, 'time-series', 2), ('polyaxon/datatile', 0.5291432738304138, 'pandas', 2), ('explosion/thinc', 0.5290007591247559, 'ml-dl', 4), ('gradio-app/gradio', 0.5276086926460266, 'viz', 3), ('fatiando/verde', 0.5272731781005859, 'gis', 1), ('alibaba/easynlp', 0.5265514850616455, 'nlp', 4), ('onnx/onnx', 0.5217620134353638, 'ml', 4), ('google/automl', 0.5180317163467407, 'ml', 2), ('salesforce/deeptime', 0.5168805718421936, 'time-series', 3), ('huggingface/transformers', 0.5144530534744263, 'nlp', 4), ('ddbourgin/numpy-ml', 0.5125497579574585, 'ml', 1), ('alkaline-ml/pmdarima', 0.5124308466911316, 'time-series', 3), ('kevinmusgrave/pytorch-metric-learning', 0.5119850635528564, 'ml', 4), ('iperov/deepfacelab', 0.5111877918243408, 'ml-dl', 2), ('lucidrains/imagen-pytorch', 0.5101648569107056, 'ml-dl', 1), ('google/trax', 0.5100558996200562, 'ml-dl', 2), ('rafiqhasan/auto-tensorflow', 0.5091307163238525, 'ml-dl', 2), ('developmentseed/label-maker', 0.5088804364204407, 'gis', 2), ('docarray/docarray', 0.5075685381889343, 'data', 3), ('polyaxon/polyaxon', 0.5069301724433899, 'ml-ops', 5), ('google/pyglove', 0.5035163164138794, 'util', 2), ('aistream-peelout/flow-forecast', 0.5033537149429321, 'time-series', 5), ('fepegar/torchio', 0.5024552941322327, 'ml-dl', 3), ('deepfakes/faceswap', 0.5015328526496887, 'ml-dl', 2), ('jindongwang/transferlearning', 0.5002632141113281, 'ml', 3)] | 114 | 5 | null | 11.42 | 414 | 252 | 54 | 0 | 5 | 7 | 5 | 413 | 511 | 90 | 1.2 | 62 |
1,883 | llm | https://github.com/apple/ml-ferret | ['ferret', 'mllm'] | Ferret: Refer and Ground Anything Anywhere at Any Granularity | [] | [] | null | null | null | apple/ml-ferret | ml-ferret | 6,445 | 331 | 111 | Python | null | null | apple | 2024-01-14 | 2023-10-06 | 16 | 388.922414 | https://avatars.githubusercontent.com/u/10639145?v=4 | Ferret: Refer and Ground Anything Anywhere at Any Granularity | [] | ['ferret', 'mllm'] | 2023-12-15 | [] | 1 | 1 | null | 0.06 | 8 | 1 | 3 | 1 | 0 | 0 | 0 | 8 | 27 | 90 | 3.4 | 62 |
1,806 | llm | https://github.com/mit-han-lab/streaming-llm | ['attention', 'long-dialogue'] | null | [] | [] | null | null | null | mit-han-lab/streaming-llm | streaming-llm | 5,807 | 335 | 61 | Python | https://arxiv.org/abs/2309.17453 | Efficient Streaming Language Models with Attention Sinks | mit-han-lab | 2024-01-14 | 2023-09-29 | 17 | 330.479675 | https://avatars.githubusercontent.com/u/39571499?v=4 | Efficient Streaming Language Models with Attention Sinks | [] | ['attention', 'long-dialogue'] | 2023-10-25 | [('freedomintelligence/llmzoo', 0.5750225782394409, 'llm', 0), ('juncongmoo/pyllama', 0.5574493408203125, 'llm', 0), ('bytedance/lightseq', 0.5517858862876892, 'nlp', 0), ('srush/minichain', 0.5470554232597351, 'llm', 0), ('thudm/chatglm-6b', 0.5384843945503235, 'llm', 0), ('eleutherai/lm-evaluation-harness', 0.5352895259857178, 'llm', 0), ('hannibal046/awesome-llm', 0.5322656035423279, 'study', 0), ('ai21labs/lm-evaluation', 0.5273094773292542, 'llm', 0), ('fasteval/fasteval', 0.5244007110595703, 'llm', 0), ('huggingface/text-generation-inference', 0.5219200253486633, 'llm', 0), ('lm-sys/fastchat', 0.5120673179626465, 'llm', 0), ('jonasgeiping/cramming', 0.5054171681404114, 'nlp', 0), ('lvwerra/trl', 0.5007056593894958, 'llm', 0), ('sjtu-ipads/powerinfer', 0.5003539323806763, 'llm', 0)] | 5 | 3 | null | 0.48 | 41 | 16 | 4 | 3 | 0 | 0 | 0 | 41 | 49 | 90 | 1.2 | 62 |
538 | util | https://github.com/mamba-org/mamba | ['package-manager', 'packaging'] | null | [] | [] | null | null | null | mamba-org/mamba | mamba | 5,690 | 322 | 45 | C++ | https://mamba.readthedocs.io | The Fast Cross-Platform Package Manager | mamba-org | 2024-01-13 | 2019-03-05 | 256 | 22.226563 | https://avatars.githubusercontent.com/u/66118895?v=4 | The Fast Cross-Platform Package Manager | ['conda', 'cpp', 'package-manager'] | ['conda', 'cpp', 'package-manager', 'packaging'] | 2024-01-11 | [('conda/conda', 0.752036988735199, 'util', 3), ('mamba-org/boa', 0.7310133576393127, 'util', 1), ('mamba-org/quetz', 0.699140191078186, 'util', 1), ('indygreg/pyoxidizer', 0.6980676651000977, 'util', 2), ('conda/conda-build', 0.6777679920196533, 'util', 1), ('spack/spack', 0.6774295568466187, 'util', 1), ('pomponchik/instld', 0.6645695567131042, 'util', 1), ('mitsuhiko/rye', 0.6489464044570923, 'util', 2), ('conda/conda-pack', 0.6462101340293884, 'util', 1), ('pdm-project/pdm', 0.6015645861625671, 'util', 2), ('python-poetry/poetry', 0.5992787480354309, 'util', 2), ('pypa/flit', 0.5987750291824341, 'util', 2), ('conda/constructor', 0.5558754801750183, 'util', 1), ('pypa/hatch', 0.5550651550292969, 'util', 2), ('pyodide/micropip', 0.5484160780906677, 'util', 0), ('tiiuae/sbomnix', 0.5184597373008728, 'util', 0), ('conda-forge/conda-smithy', 0.5094754695892334, 'util', 0), ('mamba-org/gator', 0.5042513012886047, 'jupyter', 1), ('fastai/fastcore', 0.5001938343048096, 'util', 0)] | 146 | 5 | null | 8.25 | 287 | 195 | 59 | 0 | 21 | 61 | 21 | 285 | 513 | 90 | 1.8 | 62 |
1,878 | llm | https://github.com/microsoft/promptbase | ['prompt-engineering'] | promptbase is an evolving collection of resources, best practices, and example scripts for eliciting the best performance from foundation models. | [] | [] | null | null | null | microsoft/promptbase | promptbase | 4,433 | 302 | 51 | Python | null | All things prompt engineering | microsoft | 2024-01-14 | 2023-12-12 | 7 | 633.285714 | https://avatars.githubusercontent.com/u/6154722?v=4 | All things prompt engineering | [] | ['prompt-engineering'] | 2024-01-13 | [('hazyresearch/ama_prompting', 0.7119161486625671, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.6507399082183838, 'llm', 1), ('hazyresearch/manifest', 0.629546046257019, 'llm', 1), ('promptslab/awesome-prompt-engineering', 0.56931471824646, 'study', 1), ('promptslab/promptify', 0.5429252982139587, 'nlp', 1)] | 6 | 2 | null | 0.69 | 34 | 25 | 1 | 0 | 0 | 0 | 0 | 34 | 14 | 90 | 0.4 | 62 |
1,899 | data | https://github.com/superduperdb/superduperdb | [] | null | [] | [] | null | null | null | superduperdb/superduperdb | superduperdb | 3,863 | 500 | 34 | Python | https://superduperdb.com | 🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search. | superduperdb | 2024-01-17 | 2022-08-30 | 74 | 52.202703 | https://avatars.githubusercontent.com/u/120034956?v=4 | 🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search. | ['ai', 'chatbot', 'data', 'database', 'distributed-ml', 'inference', 'llm-inference', 'llm-serving', 'llmops', 'ml', 'mlops', 'mongodb', 'pretrained-models', 'pytorch', 'semantic-search', 'sklearn', 'torch', 'transformers', 'vector-search'] | ['ai', 'chatbot', 'data', 'database', 'distributed-ml', 'inference', 'llm-inference', 'llm-serving', 'llmops', 'ml', 'mlops', 'mongodb', 'pretrained-models', 'pytorch', 'semantic-search', 'sklearn', 'torch', 'transformers', 'vector-search'] | 2024-01-16 | [('activeloopai/deeplake', 0.7059310674667358, 'ml-ops', 5), ('mindsdb/mindsdb', 0.6333754658699036, 'data', 6), ('featureform/embeddinghub', 0.6010522246360779, 'nlp', 2), ('lancedb/lancedb', 0.6009349226951599, 'data', 1), ('pathwaycom/llm-app', 0.595395028591156, 'llm', 2), ('mosaicml/composer', 0.5755331516265869, 'ml-dl', 1), ('transformeroptimus/superagi', 0.5671401023864746, 'llm', 2), ('kubeflow-kale/kale', 0.5663890838623047, 'ml-ops', 0), ('avaiga/taipy', 0.5622673034667969, 'data', 1), ('mage-ai/mage-ai', 0.5560696125030518, 'ml-ops', 1), ('bigscience-workshop/petals', 0.5544981360435486, 'data', 3), ('deepset-ai/haystack', 0.5523344278335571, 'llm', 4), ('qdrant/qdrant', 0.5490362644195557, 'data', 2), ('bentoml/bentoml', 0.5483355522155762, 'ml-ops', 3), ('cheshire-cat-ai/core', 0.547654926776886, 'llm', 3), ('netflix/metaflow', 0.542826235294342, 'ml-ops', 3), ('googlecloudplatform/vertex-ai-samples', 0.5415635704994202, 'ml', 3), ('ray-project/ray', 0.5404704809188843, 'ml-ops', 2), ('feast-dev/feast', 0.530910313129425, 'ml-ops', 2), ('airbytehq/airbyte', 0.5290766954421997, 'data', 1), ('mlflow/mlflow', 0.522727370262146, 'ml-ops', 2), ('huggingface/datasets', 0.5187201499938965, 'nlp', 1), ('hpcaitech/colossalai', 0.514103353023529, 'llm', 2), ('pathwaycom/pathway', 0.5140187740325928, 'data', 1), ('dgarnitz/vectorflow', 0.5114015340805054, 'data', 1), ('nebuly-ai/nebullvm', 0.5111740827560425, 'perf', 1), ('polyaxon/datatile', 0.5108543634414673, 'pandas', 2), ('merantix-momentum/squirrel-core', 0.5102357268333435, 'ml', 3), ('skypilot-org/skypilot', 0.5078701376914978, 'llm', 1), ('streamlit/streamlit', 0.5076687932014465, 'viz', 0), ('milvus-io/bootcamp', 0.5059596300125122, 'data', 0), ('jina-ai/jina', 0.5026459097862244, 'ml', 2), ('mlc-ai/mlc-llm', 0.5006630420684814, 'llm', 0), ('polyaxon/polyaxon', 0.5004454851150513, 'ml-ops', 3)] | 37 | 1 | null | 25.54 | 712 | 579 | 17 | 0 | 18 | 14 | 18 | 712 | 558 | 90 | 0.8 | 62 |
1,407 | llm | https://github.com/luodian/otter | ['multi-modality'] | null | [] | [] | null | null | null | luodian/otter | Otter | 3,311 | 276 | 101 | Python | https://otter-ntu.github.io/ | 🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability. | luodian | 2024-01-13 | 2023-04-01 | 43 | 76.240132 | null | 🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability. | ['apple-vision-pro', 'artificial-inteligence', 'chatgpt', 'deep-learning', 'egocentric-vision', 'embodied', 'embodied-ai', 'foundation-models', 'gpt-4', 'instruction-tuning', 'large-scale-models', 'machine-learning', 'multi-modality', 'visual-language-learning'] | ['apple-vision-pro', 'artificial-inteligence', 'chatgpt', 'deep-learning', 'egocentric-vision', 'embodied', 'embodied-ai', 'foundation-models', 'gpt-4', 'instruction-tuning', 'large-scale-models', 'machine-learning', 'multi-modality', 'visual-language-learning'] | 2023-12-30 | [('facebookresearch/habitat-lab', 0.5644159913063049, 'sim', 1), ('haotian-liu/llava', 0.5594356060028076, 'llm', 6), ('minedojo/voyager', 0.5513647794723511, 'llm', 0), ('nvlabs/prismer', 0.5447686314582825, 'diffusion', 0), ('open-mmlab/mmediting', 0.53682941198349, 'ml', 1), ('christoschristofidis/awesome-deep-learning', 0.5302937030792236, 'study', 2), ('jina-ai/finetuner', 0.5296557545661926, 'ml', 0), ('mnotgod96/appagent', 0.5246831774711609, 'llm', 1), ('nvidia/deeplearningexamples', 0.52414870262146, 'ml-dl', 1), ('jina-ai/jina', 0.5234236121177673, 'ml', 2), ('extreme-bert/extreme-bert', 0.5146451592445374, 'llm', 2), ('prefecthq/marvin', 0.5130387544631958, 'nlp', 0), ('huggingface/autotrain-advanced', 0.5102346539497375, 'ml', 2), ('ofa-sys/ofa', 0.5090562701225281, 'llm', 0), ('mlc-ai/mlc-llm', 0.5079561471939087, 'llm', 0), ('facebookresearch/mmf', 0.5072057843208313, 'ml-dl', 1), ('unity-technologies/ml-agents', 0.5054410099983215, 'ml-rl', 2), ('jina-ai/clip-as-service', 0.5049297213554382, 'nlp', 2), ('next-gpt/next-gpt', 0.501610517501831, 'llm', 5)] | 12 | 3 | null | 9.17 | 47 | 30 | 10 | 0 | 3 | 4 | 3 | 47 | 104 | 90 | 2.2 | 62 |
1,287 | llm | https://github.com/eth-sri/lmql | [] | null | [] | [] | null | null | null | eth-sri/lmql | lmql | 2,903 | 157 | 20 | Python | https://lmql.ai | A language for constraint-guided and efficient LLM programming. | eth-sri | 2024-01-14 | 2022-11-24 | 61 | 47.039352 | https://avatars.githubusercontent.com/u/5363413?v=4 | A language for constraint-guided and efficient LLM programming. | ['chatgpt', 'gpt-3', 'huggingface', 'language-model', 'programming-language'] | ['chatgpt', 'gpt-3', 'huggingface', 'language-model', 'programming-language'] | 2024-01-09 | [('guidance-ai/guidance', 0.6066431999206543, 'llm', 2), ('microsoft/autogen', 0.5932376384735107, 'llm', 1), ('bobazooba/xllm', 0.5887289047241211, 'llm', 1), ('next-gpt/next-gpt', 0.5689839124679565, 'llm', 1), ('hiyouga/llama-factory', 0.5669615268707275, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5669613480567932, 'llm', 1), ('dylanhogg/llmgraph', 0.5644213557243347, 'ml', 1), ('hwchase17/langchain', 0.5619138479232788, 'llm', 1), ('li-plus/chatglm.cpp', 0.5538818836212158, 'llm', 0), ('salesforce/codet5', 0.5481631755828857, 'nlp', 1), ('lupantech/chameleon-llm', 0.5429258942604065, 'llm', 2), ('farizrahman4u/loopgpt', 0.5417187809944153, 'llm', 1), ('killianlucas/open-interpreter', 0.5410472750663757, 'llm', 1), ('xtekky/gpt4free', 0.529441237449646, 'llm', 3), ('lianjiatech/belle', 0.5279043316841125, 'llm', 0), ('citadel-ai/langcheck', 0.5266656279563904, 'llm', 1), ('nvidia/tensorrt-llm', 0.524734616279602, 'viz', 1), ('stanfordnlp/dspy', 0.516359806060791, 'llm', 0), ('nomic-ai/gpt4all', 0.5151371955871582, 'llm', 1), ('exaloop/codon', 0.5149834752082825, 'perf', 0), ('pyomo/pyomo', 0.5141502022743225, 'math', 0), ('reasoning-machines/pal', 0.5124557018280029, 'llm', 1), ('juncongmoo/pyllama', 0.5070822834968567, 'llm', 0), ('promptslab/promptify', 0.5044764876365662, 'nlp', 2), ('h2oai/h2o-llmstudio', 0.5039780139923096, 'llm', 1), ('confident-ai/deepeval', 0.5033408403396606, 'testing', 2), ('explosion/spacy-llm', 0.502147376537323, 'llm', 1), ('langchain-ai/langgraph', 0.5018105506896973, 'llm', 0)] | 34 | 3 | null | 15.31 | 78 | 32 | 14 | 0 | 9 | 17 | 9 | 78 | 156 | 90 | 2 | 62 |
1,232 | llm | https://github.com/nvidia/nemo-guardrails | ['language-model', 'guardrails'] | null | [] | [] | null | null | null | nvidia/nemo-guardrails | NeMo-Guardrails | 2,823 | 228 | 31 | Python | null | NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems. | nvidia | 2024-01-14 | 2023-04-18 | 41 | 68.853659 | https://avatars.githubusercontent.com/u/1728152?v=4 | NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems. | [] | ['guardrails', 'language-model'] | 2024-01-12 | [('guardrails-ai/guardrails', 0.654189944267273, 'llm', 0), ('nomic-ai/gpt4all', 0.583074152469635, 'llm', 1), ('hwchase17/langchain', 0.5671313405036926, 'llm', 1), ('llm-tuning-safety/llms-finetuning-safety', 0.5286512970924377, 'llm', 0), ('tigerlab-ai/tiger', 0.527998149394989, 'llm', 0), ('nat/openplayground', 0.5180691480636597, 'llm', 1), ('aiwaves-cn/agents', 0.5130923986434937, 'nlp', 1), ('embedchain/embedchain', 0.5097015500068665, 'llm', 0), ('openlmlab/moss', 0.504492461681366, 'llm', 1), ('microsoft/autogen', 0.5011264681816101, 'llm', 0)] | 30 | 2 | null | 12.65 | 105 | 45 | 9 | 0 | 6 | 12 | 6 | 105 | 212 | 90 | 2 | 62 |
1,711 | llm | https://github.com/guardrails-ai/guardrails | [] | null | [] | [] | null | null | null | guardrails-ai/guardrails | guardrails | 2,693 | 179 | 23 | Python | https://docs.guardrailsai.com/ | Adding guardrails to large language models. | guardrails-ai | 2024-01-14 | 2023-01-29 | 52 | 51.505464 | https://avatars.githubusercontent.com/u/140440022?v=4 | Adding guardrails to large language models. | ['ai', 'foundation-model', 'gpt-3', 'llm', 'openai'] | ['ai', 'foundation-model', 'gpt-3', 'llm', 'openai'] | 2024-01-10 | [('nvidia/nemo-guardrails', 0.654189944267273, 'llm', 0), ('juncongmoo/pyllama', 0.6344968676567078, 'llm', 0), ('optimalscale/lmflow', 0.6163129210472107, 'llm', 0), ('llm-tuning-safety/llms-finetuning-safety', 0.6136285066604614, 'llm', 1), ('lianjiatech/belle', 0.6092329621315002, 'llm', 0), ('hannibal046/awesome-llm', 0.6082257032394409, 'study', 0), ('microsoft/autogen', 0.6005452871322632, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5916648507118225, 'llm', 0), ('guidance-ai/guidance', 0.578825056552887, 'llm', 0), ('lupantech/chameleon-llm', 0.5615499019622803, 'llm', 3), ('tigerlab-ai/tiger', 0.5576193928718567, 'llm', 1), ('xtekky/gpt4free', 0.5575733184814453, 'llm', 2), ('bobazooba/xllm', 0.5430307984352112, 'llm', 2), ('minimaxir/gpt-2-simple', 0.5327882766723633, 'llm', 1), ('next-gpt/next-gpt', 0.5325504541397095, 'llm', 1), ('nvidia/tensorrt-llm', 0.5297648906707764, 'viz', 0), ('aiwaves-cn/agents', 0.528048038482666, 'nlp', 1), ('mlc-ai/mlc-llm', 0.527996301651001, 'llm', 1), ('lm-sys/fastchat', 0.525242269039154, 'llm', 0), ('explosion/spacy-llm', 0.5183983445167542, 'llm', 3), ('microsoft/lmops', 0.5142502784729004, 'llm', 1), ('cg123/mergekit', 0.511229395866394, 'llm', 1), ('rafiqhasan/auto-tensorflow', 0.5081257224082947, 'ml-dl', 0), ('prefecthq/marvin', 0.5055996179580688, 'nlp', 3), ('langchain-ai/langgraph', 0.5052242875099182, 'llm', 0), ('openai/tiktoken', 0.5039165019989014, 'nlp', 0), ('ai21labs/lm-evaluation', 0.5022191405296326, 'llm', 0)] | 36 | 3 | null | 11.83 | 202 | 167 | 12 | 0 | 23 | 41 | 23 | 202 | 211 | 90 | 1 | 62 |
1,750 | data | https://github.com/giskard-ai/giskard | [] | null | [] | [] | null | null | null | giskard-ai/giskard | giskard | 2,471 | 171 | 19 | Python | https://docs.giskard.ai | 🐢 The testing framework for ML models, from tabular to LLMs | giskard-ai | 2024-01-12 | 2022-03-06 | 99 | 24.88777 | https://avatars.githubusercontent.com/u/71782571?v=4 | 🐢 The testing framework for ML models, from tabular to LLMs | ['ai-safety', 'ai-testing', 'artificial-intelligence', 'cicd', 'ethical-artificial-intelligence', 'explainable-ai', 'fairness-ai', 'llmops', 'machine-learning', 'machine-learning-testing', 'ml-safety', 'ml-testing', 'ml-validation', 'mlops', 'model-testing', 'model-validation', 'quality-assurance', 'responsible-ai', 'responsible-ml', 'trustworthy-ai'] | ['ai-safety', 'ai-testing', 'artificial-intelligence', 'cicd', 'ethical-artificial-intelligence', 'explainable-ai', 'fairness-ai', 'llmops', 'machine-learning', 'machine-learning-testing', 'ml-safety', 'ml-testing', 'ml-validation', 'mlops', 'model-testing', 'model-validation', 'quality-assurance', 'responsible-ai', 'responsible-ml', 'trustworthy-ai'] | 2024-01-12 | [('arize-ai/phoenix', 0.6145030856132507, 'ml-interpretability', 2), ('confident-ai/deepeval', 0.5690423250198364, 'testing', 1), ('ludwig-ai/ludwig', 0.5647245049476624, 'ml-ops', 1), ('interpretml/interpret', 0.5559372305870056, 'ml-interpretability', 3), ('microsoft/lmops', 0.5501245260238647, 'llm', 0), ('deepchecks/deepchecks', 0.550081193447113, 'data', 3), ('csinva/imodels', 0.5474556088447571, 'ml', 3), ('nccr-itmo/fedot', 0.5448036789894104, 'ml-ops', 1), ('mindsdb/mindsdb', 0.5253748893737793, 'data', 2), ('googlecloudplatform/vertex-ai-samples', 0.5234065651893616, 'ml', 1), ('bentoml/bentoml', 0.5216226577758789, 'ml-ops', 3), ('lastmile-ai/aiconfig', 0.5168980360031128, 'util', 0), ('tigerlab-ai/tiger', 0.5133479237556458, 'llm', 1), ('eugeneyan/testing-ml', 0.5097730755805969, 'testing', 1), ('llmware-ai/llmware', 0.5087332725524902, 'llm', 1), ('feast-dev/feast', 0.507591962814331, 'ml-ops', 2), ('mlflow/mlflow', 0.5059633851051331, 'ml-ops', 1), ('polyaxon/polyaxon', 0.5021538734436035, 'ml-ops', 3)] | 40 | 4 | null | 95.15 | 437 | 411 | 23 | 0 | 36 | 27 | 36 | 437 | 627 | 90 | 1.4 | 62 |
1,721 | viz | https://github.com/mckinsey/vizro | [] | null | [] | [] | null | null | null | mckinsey/vizro | vizro | 2,136 | 91 | 14 | Python | https://vizro.readthedocs.io/en/stable/ | Vizro is a toolkit for creating modular data visualization applications. | mckinsey | 2024-01-14 | 2023-09-04 | 21 | 101.027027 | https://avatars.githubusercontent.com/u/4265350?v=4 | Vizro is a toolkit for creating modular data visualization applications. | ['dashboard', 'data-visualization', 'plotly', 'plotly-dash', 'pydantic', 'visualization'] | ['dashboard', 'data-visualization', 'plotly', 'plotly-dash', 'pydantic', 'visualization'] | 2024-01-11 | [('man-group/dtale', 0.584793746471405, 'viz', 3), ('holoviz/panel', 0.5707153081893921, 'viz', 1), ('visgl/deck.gl', 0.5679866671562195, 'viz', 2), ('pyvista/pyvista', 0.5597613453865051, 'viz', 1), ('gaogaotiantian/viztracer', 0.5495272874832153, 'profiling', 1), ('holoviz/holoviz', 0.5490374565124512, 'viz', 0), ('bokeh/bokeh', 0.5383272171020508, 'viz', 1), ('pyqtgraph/pyqtgraph', 0.5374338626861572, 'viz', 1), ('mwaskom/seaborn', 0.535768449306488, 'viz', 1), ('nomic-ai/deepscatter', 0.5346618294715881, 'viz', 2), ('altair-viz/altair', 0.5226520895957947, 'viz', 1), ('polyaxon/datatile', 0.5210312008857727, 'pandas', 2), ('saulpw/visidata', 0.517253577709198, 'term', 0), ('mitvis/vistext', 0.5145730972290039, 'data', 0), ('gregorhd/mapcompare', 0.506889283657074, 'gis', 0), ('residentmario/geoplot', 0.5022686719894409, 'gis', 0)] | 15 | 2 | null | 3.54 | 161 | 134 | 4 | 0 | 11 | 33 | 11 | 161 | 194 | 90 | 1.2 | 62 |
55 | ml-rl | https://github.com/openai/gym | ['reinforcement-learning'] | null | [] | [] | null | null | null | openai/gym | gym | 33,375 | 8,704 | 1,061 | Python | https://www.gymlibrary.dev | A toolkit for developing and comparing reinforcement learning algorithms. | openai | 2024-01-14 | 2016-04-27 | 404 | 82.436486 | https://avatars.githubusercontent.com/u/14957082?v=4 | A toolkit for developing and comparing reinforcement learning algorithms. | [] | ['reinforcement-learning'] | 2023-01-30 | [('shangtongzhang/reinforcement-learning-an-introduction', 0.6223573088645935, 'study', 1), ('deepmind/acme', 0.6127493381500244, 'ml-rl', 1), ('pytorch/rl', 0.5818626880645752, 'ml-rl', 1), ('thu-ml/tianshou', 0.5749742984771729, 'ml-rl', 0), ('facebookresearch/reagent', 0.573969841003418, 'ml-rl', 0), ('google/dopamine', 0.5587803721427917, 'ml-rl', 0), ('openai/baselines', 0.5574614405632019, 'ml-rl', 0), ('pettingzoo-team/pettingzoo', 0.5399578213691711, 'ml-rl', 1), ('unity-technologies/ml-agents', 0.5394145846366882, 'ml-rl', 1), ('humancompatibleai/imitation', 0.5389503836631775, 'ml-rl', 0), ('farama-foundation/gymnasium', 0.533967137336731, 'ml-rl', 1), ('kzl/decision-transformer', 0.5008352994918823, 'ml-rl', 0), ('denys88/rl_games', 0.5007779598236084, 'ml-rl', 1), ('arise-initiative/robosuite', 0.500554084777832, 'ml-rl', 1)] | 384 | 3 | null | 0.04 | 23 | 10 | 94 | 12 | 0 | 7 | 7 | 23 | 29 | 90 | 1.3 | 61 |
1,082 | security | https://github.com/sqlmapproject/sqlmap | [] | null | [] | [] | null | null | null | sqlmapproject/sqlmap | sqlmap | 29,583 | 5,602 | 1,090 | Python | http://sqlmap.org | Automatic SQL injection and database takeover tool | sqlmapproject | 2024-01-14 | 2012-06-26 | 605 | 48.897521 | https://avatars.githubusercontent.com/u/735289?v=4 | Automatic SQL injection and database takeover tool | ['database', 'detection', 'exploitation', 'pentesting', 'sql-injection', 'sqlmap', 'takeover', 'vulnerability-scanner'] | ['database', 'detection', 'exploitation', 'pentesting', 'sql-injection', 'sqlmap', 'takeover', 'vulnerability-scanner'] | 2024-01-11 | [('swisskyrepo/payloadsallthethings', 0.5263312458992004, 'security', 0)] | 133 | 3 | null | 2.38 | 73 | 64 | 141 | 0 | 1 | 9 | 1 | 73 | 84 | 90 | 1.2 | 61 |
467 | util | https://github.com/alievk/avatarify-python | [] | null | [] | [] | null | null | null | alievk/avatarify-python | avatarify-python | 15,989 | 3,217 | 317 | Python | null | Avatars for Zoom, Skype and other video-conferencing apps. | alievk | 2024-01-13 | 2020-04-06 | 199 | 80.289096 | null | Avatars for Zoom, Skype and other video-conferencing apps. | [] | [] | 2023-09-29 | [] | 24 | 5 | null | 0.08 | 54 | 14 | 46 | 4 | 0 | 1 | 1 | 54 | 165 | 90 | 3.1 | 61 |
331 | ml-rl | https://github.com/unity-technologies/ml-agents | [] | null | [] | [] | null | null | null | unity-technologies/ml-agents | ml-agents | 15,866 | 4,039 | 551 | C# | https://unity.com/products/machine-learning-agents | The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning. | unity-technologies | 2024-01-14 | 2017-09-08 | 333 | 47.564026 | https://avatars.githubusercontent.com/u/426196?v=4 | The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning. | ['deep-learning', 'deep-reinforcement-learning', 'machine-learning', 'neural-networks', 'reinforcement-learning', 'unity', 'unity3d'] | ['deep-learning', 'deep-reinforcement-learning', 'machine-learning', 'neural-networks', 'reinforcement-learning', 'unity', 'unity3d'] | 2023-12-02 | [('facebookresearch/habitat-lab', 0.6679417490959167, 'sim', 3), ('salesforce/warp-drive', 0.6577045321464539, 'ml-rl', 2), ('google/dopamine', 0.6415248513221741, 'ml-rl', 0), ('tensorflow/tensor2tensor', 0.6379924416542053, 'ml', 3), ('inspirai/timechamber', 0.6286770105361938, 'sim', 2), ('keras-rl/keras-rl', 0.6218107342720032, 'ml-rl', 3), ('pytorch/rl', 0.6213619709014893, 'ml-rl', 2), ('farama-foundation/gymnasium', 0.6212126612663269, 'ml-rl', 1), ('tensorlayer/tensorlayer', 0.61866694688797, 'ml-rl', 2), ('pettingzoo-team/pettingzoo', 0.6170148849487305, 'ml-rl', 1), ('deepmind/dm_control', 0.6150110363960266, 'ml-rl', 4), ('google/trax', 0.5988940596580505, 'ml-dl', 4), ('thu-ml/tianshou', 0.598300576210022, 'ml-rl', 0), ('operand/agency', 0.596383810043335, 'llm', 1), ('mlflow/mlflow', 0.5918627381324768, 'ml-ops', 1), ('arise-initiative/robosuite', 0.58687424659729, 'ml-rl', 1), ('openai/spinningup', 0.5850274562835693, 'study', 0), ('tensorflow/tensorflow', 0.5806676149368286, 'ml-dl', 2), ('nvidia-omniverse/orbit', 0.5719271898269653, 'sim', 0), ('bentoml/bentoml', 0.5712394714355469, 'ml-ops', 2), ('googlecloudplatform/vertex-ai-samples', 0.5682862997055054, 'ml', 0), ('openai/baselines', 0.5591613054275513, 'ml-rl', 0), ('denys88/rl_games', 0.5579639077186584, 'ml-rl', 2), ('microsoft/onnxruntime', 0.5510517358779907, 'ml', 3), ('microsoft/nni', 0.5489663481712341, 'ml', 2), ('ray-project/ray', 0.5486295223236084, 'ml-ops', 3), ('oegedijk/explainerdashboard', 0.5465452671051025, 'ml-interpretability', 0), ('polyaxon/polyaxon', 0.5450904965400696, 'ml-ops', 3), ('ddbourgin/numpy-ml', 0.5443470478057861, 'ml', 3), ('determined-ai/determined', 0.5427035689353943, 'ml-ops', 2), ('transformeroptimus/superagi', 0.5418506264686584, 'llm', 0), ('slundberg/shap', 0.5413389205932617, 'ml-interpretability', 2), ('prefecthq/marvin', 0.5411503911018372, 'nlp', 0), ('openai/gym', 0.5394145846366882, 'ml-rl', 1), ('google-research/language', 0.5368104577064514, 'nlp', 1), ('nvidia/deeplearningexamples', 0.5343484878540039, 'ml-dl', 1), ('nvidia-omniverse/omniisaacgymenvs', 0.5333084464073181, 'sim', 0), ('deepchecks/deepchecks', 0.5319340825080872, 'data', 2), ('antonosika/gpt-engineer', 0.5287721157073975, 'llm', 0), ('huggingface/datasets', 0.5283746719360352, 'nlp', 2), ('onnx/onnx', 0.5283321142196655, 'ml', 2), ('facebookresearch/reagent', 0.5251111388206482, 'ml-rl', 0), ('humancompatibleai/imitation', 0.5231532454490662, 'ml-rl', 0), ('alirezadir/machine-learning-interview-enlightener', 0.5230525732040405, 'study', 2), ('projectmesa/mesa', 0.5214616060256958, 'sim', 0), ('deepmind/pysc2', 0.5204218029975891, 'ml-rl', 2), ('ai4finance-foundation/finrl', 0.5189048647880554, 'finance', 2), ('explosion/thinc', 0.5183029174804688, 'ml-dl', 2), ('pytorchlightning/pytorch-lightning', 0.5169978737831116, 'ml-dl', 2), ('deeppavlov/deeppavlov', 0.5153900980949402, 'nlp', 2), ('microsoft/lmops', 0.5131751298904419, 'llm', 0), ('krohling/bondai', 0.5124642252922058, 'llm', 0), ('zacwellmer/worldmodels', 0.5110092163085938, 'ml-rl', 0), ('keras-team/keras', 0.5099013447761536, 'ml-dl', 3), ('koaning/human-learn', 0.5095399618148804, 'data', 1), ('deepmind/acme', 0.5082459449768066, 'ml-rl', 1), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5079880356788635, 'study', 2), ('mlc-ai/mlc-llm', 0.5073363184928894, 'llm', 0), ('aiqc/aiqc', 0.5059369802474976, 'ml-ops', 0), ('luodian/otter', 0.5054410099983215, 'llm', 2), ('rasbt/machine-learning-book', 0.5040963292121887, 'study', 3), ('hpcaitech/colossalai', 0.5021815896034241, 'llm', 1), ('ml-tooling/opyrator', 0.5017167925834656, 'viz', 1), ('rasbt/deeplearning-models', 0.501521110534668, 'ml-dl', 0)] | 161 | 5 | null | 0.81 | 68 | 49 | 77 | 1 | 1 | 22 | 1 | 68 | 154 | 90 | 2.3 | 61 |
550 | ml-ops | https://github.com/horovod/horovod | [] | null | [] | ['horovod'] | null | null | null | horovod/horovod | horovod | 13,750 | 2,227 | 331 | Python | http://horovod.ai | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. | horovod | 2024-01-13 | 2017-08-09 | 337 | 40.697674 | https://avatars.githubusercontent.com/u/46361271?v=4 | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. | ['baidu', 'deep-learning', 'deeplearning', 'keras', 'machine-learning', 'machinelearning', 'mpi', 'mxnet', 'pytorch', 'ray', 'spark', 'tensorflow', 'uber'] | ['baidu', 'deep-learning', 'deeplearning', 'keras', 'machine-learning', 'machinelearning', 'mpi', 'mxnet', 'pytorch', 'ray', 'spark', 'tensorflow', 'uber'] | 2024-01-05 | [('paddlepaddle/paddle', 0.7518745064735413, 'ml-dl', 2), ('tensorflow/tensorflow', 0.7118455767631531, 'ml-dl', 3), ('determined-ai/determined', 0.6985735297203064, 'ml-ops', 5), ('microsoft/deepspeed', 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1,021 | finance | https://github.com/microsoft/qlib | [] | null | [] | [] | 1 | null | null | microsoft/qlib | qlib | 13,247 | 2,302 | 275 | Python | https://qlib.readthedocs.io/en/latest/ | Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL. | microsoft | 2024-01-14 | 2020-08-14 | 180 | 73.361551 | https://avatars.githubusercontent.com/u/6154722?v=4 | Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL. | ['algorithmic-trading', 'auto-quant', 'deep-learning', 'finance', 'fintech', 'investment', 'machine-learning', 'paper', 'platform', 'quant', 'quant-dataset', 'quant-models', 'quantitative-finance', 'quantitative-trading', 'research', 'research-paper', 'stock-data'] | ['algorithmic-trading', 'auto-quant', 'deep-learning', 'finance', 'fintech', 'investment', 'machine-learning', 'paper', 'platform', 'quant', 'quant-dataset', 'quant-models', 'quantitative-finance', 'quantitative-trading', 'research', 'research-paper', 'stock-data'] | 2023-11-21 | [('ai4finance-foundation/finrl', 0.5603201389312744, 'finance', 3), ('zvtvz/zvt', 0.5502883791923523, 'finance', 6), ('goldmansachs/gs-quant', 0.5478851199150085, 'finance', 0), ('google/tf-quant-finance', 0.5447477698326111, 'finance', 2), ('chancefocus/pixiu', 0.5296194553375244, 'finance', 2), ('quantconnect/lean', 0.5189212560653687, 'finance', 1), ('openbb-finance/openbbterminal', 0.5187370777130127, 'finance', 4), ('xplainable/xplainable', 0.5183536410331726, 'ml-interpretability', 1), ('ranaroussi/quantstats', 0.5154274702072144, 'finance', 5), ('tensorflow/tensor2tensor', 0.5105899572372437, 'ml', 2), ('numerai/example-scripts', 0.5105475187301636, 'finance', 1), ('quantecon/quantecon.py', 0.5021764636039734, 'sim', 0)] | 122 | 3 | null | 1.12 | 178 | 118 | 42 | 2 | 3 | 6 | 3 | 178 | 107 | 90 | 0.6 | 61 |
849 | viz | https://github.com/visgl/deck.gl | [] | null | [] | [] | null | null | null | visgl/deck.gl | deck.gl | 11,453 | 2,061 | 1,693 | TypeScript | https://deck.gl | WebGL2 powered visualization framework | visgl | 2024-01-13 | 2015-12-15 | 424 | 27.011792 | https://avatars.githubusercontent.com/u/46735142?v=4 | WebGL2 powered visualization framework | ['data-visualization', 'geospatial-analysis', 'javascript', 'maps', 'visualization', 'webgl'] | ['data-visualization', 'geospatial-analysis', 'javascript', 'maps', 'visualization', 'webgl'] | 2024-01-12 | [('nomic-ai/deepscatter', 0.6989966630935669, 'viz', 3), ('giswqs/geemap', 0.6095970869064331, 'gis', 0), ('raphaelquast/eomaps', 0.6003251075744629, 'gis', 1), ('bokeh/bokeh', 0.5892252326011658, 'viz', 2), ('residentmario/geoplot', 0.5753275156021118, 'gis', 0), ('mckinsey/vizro', 0.5679866671562195, 'viz', 2), ('vispy/vispy', 0.5518122911453247, 'viz', 1), ('pyvista/pyvista', 0.5255587100982666, 'viz', 1), ('holoviz/datashader', 0.521821916103363, 'gis', 0), ('plotly/plotly.py', 0.5213139057159424, 'viz', 2), ('holoviz/holoviz', 0.5192416310310364, 'viz', 0), ('man-group/dtale', 0.5085725784301758, 'viz', 2), ('holoviz/panel', 0.5066721439361572, 'viz', 0)] | 243 | 3 | null | 6.06 | 207 | 137 | 98 | 0 | 57 | 72 | 57 | 207 | 193 | 90 | 0.9 | 61 |
411 | util | https://github.com/pre-commit/pre-commit | ['code-quality'] | null | [] | [] | null | null | null | pre-commit/pre-commit | pre-commit | 11,446 | 788 | 86 | Python | https://pre-commit.com | A framework for managing and maintaining multi-language pre-commit hooks. | pre-commit | 2024-01-14 | 2014-03-13 | 515 | 22.19446 | https://avatars.githubusercontent.com/u/6943086?v=4 | A framework for managing and maintaining multi-language pre-commit hooks. | ['git', 'linter', 'pre-commit', 'refactoring'] | ['code-quality', 'git', 'linter', 'pre-commit', 'refactoring'] | 2024-01-12 | [('asottile/pyupgrade', 0.6998698115348816, 'util', 3), ('psf/black', 0.5649186968803406, 'util', 1), ('thudm/codegeex', 0.5082143545150757, 'llm', 0)] | 156 | 4 | null | 2.46 | 105 | 97 | 120 | 0 | 17 | 19 | 17 | 105 | 234 | 90 | 2.2 | 61 |
1,250 | util | https://github.com/openai/triton | [] | null | [] | [] | null | null | null | openai/triton | triton | 9,513 | 1,050 | 171 | C++ | https://triton-lang.org/ | Development repository for the Triton language and compiler | openai | 2024-01-14 | 2014-08-30 | 491 | 19.357849 | https://avatars.githubusercontent.com/u/14957082?v=4 | Development repository for the Triton language and compiler | [] | [] | 2024-01-12 | [('scikit-build/scikit-build', 0.5731392502784729, 'ml', 0), ('python/cpython', 0.5405258536338806, 'util', 0), ('pytorch/glow', 0.5112419724464417, 'ml', 0), ('cython/cython', 0.502590537071228, 'util', 0), ('pypy/pypy', 0.500663697719574, 'util', 0)] | 202 | 6 | null | 18.96 | 516 | 379 | 114 | 0 | 0 | 1 | 1 | 517 | 1,005 | 90 | 1.9 | 61 |
243 | util | https://github.com/aws/serverless-application-model | [] | null | [] | [] | null | null | null | aws/serverless-application-model | serverless-application-model | 9,181 | 2,406 | 289 | Python | https://aws.amazon.com/serverless/sam | The AWS Serverless Application Model (AWS SAM) transform is a AWS CloudFormation macro that transforms SAM templates into CloudFormation templates. | aws | 2024-01-12 | 2016-10-10 | 381 | 24.088081 | https://avatars.githubusercontent.com/u/2232217?v=4 | The AWS Serverless Application Model (AWS SAM) transform is a AWS CloudFormation macro that transforms SAM templates into CloudFormation templates. | ['aws', 'aws-sam', 'lambda', 'sam', 'sam-specification', 'serverless', 'serverless-application-model', 'serverless-applications'] | ['aws', 'aws-sam', 'lambda', 'sam', 'sam-specification', 'serverless', 'serverless-application-model', 'serverless-applications'] | 2024-01-10 | [('nficano/python-lambda', 0.5357404947280884, 'util', 2), ('aws/chalice', 0.5237606167793274, 'web', 3)] | 268 | 4 | null | 8.02 | 155 | 144 | 88 | 0 | 28 | 13 | 28 | 154 | 173 | 90 | 1.1 | 61 |