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697 | util | https://github.com/openai/openai-python | [] | null | [] | [] | null | null | null | openai/openai-python | openai-python | 17,664 | 2,403 | 249 | Python | https://pypi.org/project/openai/ | The official Python library for the OpenAI API | openai | 2024-01-14 | 2020-10-25 | 170 | 103.731544 | https://avatars.githubusercontent.com/u/14957082?v=4 | The official Python library for the OpenAI API | ['openai'] | ['openai'] | 2024-01-12 | [('openai/openai-cookbook', 0.6652215123176575, 'ml', 1), ('langchain-ai/opengpts', 0.6509252190589905, 'llm', 0), ('shishirpatil/gorilla', 0.6225490570068359, 'llm', 0), ('googleapis/google-api-python-client', 0.5968145728111267, 'util', 0), ('fastai/ghapi', 0.5810590982437134, 'util', 0), ('fastai/fastcore', 0.5748746991157532, 'util', 0), ('urwid/urwid', 0.5712311267852783, 'term', 0), ('tebelorg/rpa-python', 0.5686379671096802, 'util', 0), ('kivy/kivy', 0.5627065300941467, 'util', 0), ('vitalik/django-ninja', 0.5567331910133362, 'web', 0), ('huggingface/huggingface_hub', 0.5553815960884094, 'ml', 0), ('pytoolz/toolz', 0.5484781861305237, 'util', 0), ('ipython/ipython', 0.5373437404632568, 'util', 0), ('man-c/pycoingecko', 0.5335339307785034, 'crypto', 0), ('simple-salesforce/simple-salesforce', 0.5326930284500122, 'data', 0), ('berriai/litellm', 0.5291408896446228, 'llm', 1), ('cohere-ai/cohere-python', 0.5279492735862732, 'util', 0), ('open-telemetry/opentelemetry-python', 0.5268572568893433, 'util', 0), ('open-telemetry/opentelemetry-python-contrib', 0.5244234204292297, 'util', 0), ('timofurrer/awesome-asyncio', 0.524164617061615, 'study', 0), ('larsbaunwall/bricky', 0.5239132642745972, 'llm', 1), ('kuimono/openapi-schema-pydantic', 0.52321857213974, 'util', 0), ('falconry/falcon', 0.5228433609008789, 'web', 0), ('kubeflow/fairing', 0.5159801244735718, 'ml-ops', 0), ('xtekky/gpt4free', 0.515657901763916, 'llm', 1), ('nasdaq/data-link-python', 0.5095574855804443, 'finance', 0), ('mitmproxy/pdoc', 0.5083382725715637, 'util', 0), ('hugapi/hug', 0.5053588151931763, 'util', 0), ('dylanhogg/awesome-python', 0.5051689147949219, 'study', 0), ('ta-lib/ta-lib-python', 0.5044464468955994, 'finance', 0), ('pypy/pypy', 0.5010403990745544, 'util', 0), ('cuemacro/findatapy', 0.5010272860527039, 'finance', 0), ('laion-ai/open-assistant', 0.5009532570838928, 'llm', 0), ('mamba-org/quetz', 0.5004561543464661, 'util', 0)] | 96 | 3 | null | 4.12 | 536 | 498 | 39 | 0 | 44 | 28 | 44 | 536 | 1,076 | 90 | 2 | 72 |
313 | util | https://github.com/pydantic/pydantic | ['serialization', 'parsing', 'typing', 'validation'] | null | [] | [] | 1 | null | null | pydantic/pydantic | pydantic | 17,235 | 1,579 | 104 | Python | https://docs.pydantic.dev | Data validation using Python type hints | pydantic | 2024-01-14 | 2017-05-03 | 351 | 48.982948 | https://avatars.githubusercontent.com/u/110818415?v=4 | Data validation using Python type hints | ['hints', 'json-schema', 'parsing', 'pydantic', 'python310', 'python311', 'python312', 'python37', 'python38', 'python39', 'validation'] | ['hints', 'json-schema', 'parsing', 'pydantic', 'python310', 'python311', 'python312', 'python37', 'python38', 'python39', 'serialization', 'typing', 'validation'] | 2024-01-12 | [('pyeve/cerberus', 0.7001333832740784, 'data', 0), ('python-odin/odin', 0.6526608467102051, 'util', 1), ('facebook/pyre-check', 0.6196001768112183, 'typing', 0), ('marshmallow-code/marshmallow', 0.606956422328949, 'util', 2), ('patrick-kidger/torchtyping', 0.5341143012046814, 'typing', 1), ('andialbrecht/sqlparse', 0.534013569355011, 'data', 0), ('agronholm/typeguard', 0.5333467721939087, 'typing', 0), ('wtforms/wtforms', 0.5329594612121582, 'web', 1), ('pylons/colander', 0.531548798084259, 'util', 2), ('collerek/ormar', 0.5280044078826904, 'data', 1), ('omry/omegaconf', 0.5237911343574524, 'util', 0), ('mkdocstrings/griffe', 0.5223087072372437, 'util', 0), ('tiangolo/sqlmodel', 0.5132742524147034, 'data', 2), ('microsoft/pyright', 0.5103999376296997, 'typing', 0), ('strawberry-graphql/strawberry', 0.5045525431632996, 'web', 0), ('instagram/libcst', 0.5014991164207458, 'util', 0)] | 466 | 3 | null | 23.17 | 893 | 695 | 82 | 0 | 33 | 19 | 33 | 893 | 2,136 | 90 | 2.4 | 72 |
493 | pandas | https://github.com/duckdb/duckdb | ['arrow', 'dataframe'] | null | [] | [] | 1 | null | null | duckdb/duckdb | duckdb | 13,828 | 1,273 | 161 | C++ | http://www.duckdb.org | DuckDB is an in-process SQL OLAP Database Management System | duckdb | 2024-01-14 | 2018-06-26 | 292 | 47.356164 | https://avatars.githubusercontent.com/u/82039556?v=4 | DuckDB is an in-process SQL OLAP Database Management System | ['analytics', 'database', 'embedded-database', 'olap', 'sql'] | ['analytics', 'arrow', 'database', 'dataframe', 'embedded-database', 'olap', 'sql'] | 2024-01-12 | [('duckdb/dbt-duckdb', 0.6090986132621765, 'data', 0), ('mause/duckdb_engine', 0.510148286819458, 'data', 1)] | 354 | 2 | null | 265.73 | 1,220 | 950 | 68 | 0 | 7 | 7 | 7 | 1,220 | 2,333 | 90 | 1.9 | 72 |
1,237 | llm | https://github.com/idea-research/grounded-segment-anything | [] | null | [] | [] | null | null | null | idea-research/grounded-segment-anything | Grounded-Segment-Anything | 12,205 | 1,094 | 111 | Jupyter Notebook | null | Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything | idea-research | 2024-01-14 | 2023-04-06 | 42 | 285.735786 | https://avatars.githubusercontent.com/u/113572103?v=4 | Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything | ['3d-whole-body-pose-estimation', 'automatic-labeling-system', 'caption', 'data-generation', 'image-editing', 'open-vocabulary-detection', 'open-vocabulary-segmentation', 'speech'] | ['3d-whole-body-pose-estimation', 'automatic-labeling-system', 'caption', 'data-generation', 'image-editing', 'open-vocabulary-detection', 'open-vocabulary-segmentation', 'speech'] | 2023-12-31 | [('idea-research/groundingdino', 0.6477982997894287, 'diffusion', 0), ('roboflow/notebooks', 0.6104524731636047, 'study', 3), ('open-mmlab/mmediting', 0.5329544544219971, 'ml', 1), ('roboflow/supervision', 0.525745153427124, 'ml', 0)] | 44 | 7 | null | 4.52 | 79 | 31 | 9 | 0 | 0 | 0 | 0 | 79 | 112 | 90 | 1.4 | 72 |
1,596 | llm | https://github.com/paddlepaddle/paddlenlp | [] | null | [] | [] | null | null | null | paddlepaddle/paddlenlp | PaddleNLP | 10,831 | 2,753 | 100 | Python | https://paddlenlp.readthedocs.io | π Easy-to-use and powerful NLP and LLM library with π€ Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including πText Classification, π Neural Search, β Question Answering, βΉοΈ Information Extraction, π Document Intelligence, π Sentiment Analysis etc. | paddlepaddle | 2024-01-14 | 2021-02-05 | 155 | 69.620753 | https://avatars.githubusercontent.com/u/23534030?v=4 | π Easy-to-use and powerful NLP and LLM library with π€ Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including πText Classification, π Neural Search, β Question Answering, βΉοΈ Information Extraction, π Document Intelligence, π Sentiment Analysis etc. | ['bert', 'compression', 'distributed-training', 'document-intelligence', 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1,521 | nlp | https://github.com/facebookresearch/seamless_communication | ['text-to-speech', 'speech-to-text'] | null | [] | [] | null | null | null | facebookresearch/seamless_communication | seamless_communication | 9,358 | 954 | 140 | Jupyter Notebook | null | Foundational Models for State-of-the-Art Speech and Text Translation | facebookresearch | 2024-01-14 | 2023-08-01 | 26 | 359.923077 | https://avatars.githubusercontent.com/u/16943930?v=4 | Foundational Models for State-of-the-Art Speech and Text Translation | [] | ['speech-to-text', 'text-to-speech'] | 2024-01-11 | [('pndurette/gtts', 0.5938905477523804, 'util', 1), ('openai/whisper', 0.5865522623062134, 'ml-dl', 1), ('suno-ai/bark', 0.553849995136261, 'ml', 0), ('juncongmoo/pyllama', 0.5527052879333496, 'llm', 0), ('nateshmbhat/pyttsx3', 0.5521857142448425, 'util', 1), ('next-gpt/next-gpt', 0.5332794785499573, 'llm', 0), ('infinitylogesh/mutate', 0.5298645496368408, 'nlp', 0), ('m-bain/whisperx', 0.5283752083778381, 'nlp', 1), ('thudm/chatglm-6b', 0.5281906127929688, 'llm', 0), ('nvidia/nemo', 0.5158795714378357, 'nlp', 2), ('gunthercox/chatterbot-corpus', 0.5149349570274353, 'nlp', 0), ('espnet/espnet', 0.5085058212280273, 'nlp', 0), ('openlmlab/moss', 0.5070318579673767, 'llm', 0), ('ai21labs/lm-evaluation', 0.505820631980896, 'llm', 0), ('huggingface/text-generation-inference', 0.5040040612220764, 'llm', 0)] | 29 | 6 | null | 1.79 | 159 | 85 | 6 | 0 | 0 | 0 | 0 | 159 | 174 | 90 | 1.1 | 72 |
1,901 | util | https://github.com/mitsuhiko/rye | ['dependency-manager', 'packaging', 'package-manager'] | null | [] | [] | null | null | null | mitsuhiko/rye | rye | 7,781 | 197 | 46 | Rust | https://rye-up.com | An Experimental Package Management Solution for Python | mitsuhiko | 2024-01-17 | 2023-04-22 | 40 | 192.462898 | null | An Experimental Package Management Solution for Python | ['package-manager', 'packaging'] | ['dependency-manager', 'package-manager', 'packaging'] | 2024-01-16 | [('indygreg/pyoxidizer', 0.8726885914802551, 'util', 2), ('python-poetry/poetry', 0.8581348657608032, 'util', 3), ('pypa/flit', 0.825670599937439, 'util', 2), ('pomponchik/instld', 0.748336672782898, 'util', 1), ('pdm-project/pdm', 0.7408201694488525, 'util', 2), ('pypa/hatch', 0.7138620615005493, 'util', 2), ('regebro/pyroma', 0.661931574344635, 'util', 1), ('pyodide/micropip', 0.6547753810882568, 'util', 0), ('pypi/warehouse', 0.6509472131729126, 'util', 0), ('mamba-org/mamba', 0.6489464044570923, 'util', 2), ('tox-dev/pipdeptree', 0.5925803780555725, 'util', 0), ('tezromach/python-package-template', 0.5775073170661926, 'template', 0), ('jazzband/pip-tools', 0.5770611763000488, 'util', 1), ('ofek/pyapp', 0.575480043888092, 'util', 1), ('spack/spack', 0.5651411414146423, 'util', 1), ('tiangolo/poetry-version-plugin', 0.5633344054222107, 'util', 1), ('conda/conda', 0.5606615543365479, 'util', 2), ('ivankorobkov/python-inject', 0.5525853037834167, 'util', 0), ('pytables/pytables', 0.54390549659729, 'data', 0), ('python-injector/injector', 0.5345786213874817, 'util', 0), ('mamba-org/gator', 0.5343549847602844, 'jupyter', 0), ('beeware/briefcase', 0.5340247750282288, 'util', 0), ('pypa/pipenv', 0.5276722311973572, 'util', 1), ('pypa/installer', 0.5275384187698364, 'util', 0), ('omry/omegaconf', 0.5054756999015808, 'util', 0), ('thoth-station/micropipenv', 0.5018079280853271, 'util', 0), ('mgedmin/check-manifest', 0.5007199645042419, 'util', 0)] | 52 | 3 | null | 8 | 60 | 33 | 9 | 0 | 21 | 30 | 21 | 60 | 104 | 90 | 1.7 | 72 |
1,193 | llm | https://github.com/thudm/chatglm-6b | ['language-model'] | null | [] | [] | null | null | null | thudm/chatglm-6b | ChatGLM-6B | 37,146 | 4,974 | 382 | Python | null | ChatGLM-6B: An Open Bilingual Dialogue Language Model | εΌζΊεθ―ε―Ήθ―θ―θ¨ζ¨‘ε | thudm | 2024-01-14 | 2023-03-13 | 46 | 805.021672 | https://avatars.githubusercontent.com/u/48590610?v=4 | ChatGLM-6B: An Open Bilingual Dialogue Language Model | εΌζΊεθ―ε―Ήθ―θ―θ¨ζ¨‘ε | [] | ['language-model'] | 2023-10-27 | [('thudm/chatglm2-6b', 0.7089318633079529, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.6088327765464783, 'nlp', 0), ('thudm/glm-130b', 0.5821515321731567, 'llm', 0), ('freedomintelligence/llmzoo', 0.5757870674133301, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.5738417506217957, 'llm', 1), ('openlmlab/moss', 0.556516170501709, 'llm', 1), ('suno-ai/bark', 0.552562415599823, 'ml', 0), ('mit-han-lab/streaming-llm', 0.5384843945503235, 'llm', 0), ('ctlllll/llm-toolmaker', 0.536123514175415, 'llm', 1), ('lm-sys/fastchat', 0.5337995290756226, 'llm', 1), ('baichuan-inc/baichuan-13b', 0.5303475856781006, 'llm', 0), ('guidance-ai/guidance', 0.5300068259239197, 'llm', 1), ('facebookresearch/seamless_communication', 0.5281906127929688, 'nlp', 0), ('srush/minichain', 0.5271021127700806, 'llm', 0), ('ai21labs/lm-evaluation', 0.5155556201934814, 'llm', 1)] | 49 | 4 | null | 5.29 | 97 | 36 | 10 | 3 | 0 | 0 | 0 | 97 | 112 | 90 | 1.2 | 71 |
1,104 | llm | https://github.com/openai/chatgpt-retrieval-plugin | [] | null | [] | [] | null | null | null | openai/chatgpt-retrieval-plugin | chatgpt-retrieval-plugin | 20,419 | 3,796 | 323 | Python | null | The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language. | openai | 2024-01-13 | 2023-03-23 | 44 | 456.654952 | https://avatars.githubusercontent.com/u/14957082?v=4 | The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language. | ['chatgpt', 'chatgpt-plugins'] | ['chatgpt', 'chatgpt-plugins'] | 2023-12-04 | [('langchain-ai/chat-langchain', 0.5608171820640564, 'llm', 0), ('run-llama/rags', 0.5382370948791504, 'llm', 1), ('rcgai/simplyretrieve', 0.5177233815193176, 'llm', 0), ('killianlucas/open-interpreter', 0.5168745517730713, 'llm', 1), ('h2oai/h2ogpt', 0.5049951076507568, 'llm', 1)] | 39 | 6 | null | 1.73 | 44 | 18 | 10 | 1 | 0 | 0 | 0 | 44 | 33 | 90 | 0.8 | 71 |
327 | security | https://github.com/aquasecurity/trivy | [] | null | [] | [] | null | null | null | aquasecurity/trivy | trivy | 19,961 | 2,005 | 166 | Go | https://aquasecurity.github.io/trivy | Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more | aquasecurity | 2024-01-13 | 2019-04-11 | 250 | 79.616524 | https://avatars.githubusercontent.com/u/12783832?v=4 | Find vulnerabilities, misconfigurations, secrets, SBOM in containers, Kubernetes, code repositories, clouds and more | ['containers', 'devsecops', 'docker', 'go', 'golang', 'iac', 'infrastructure-as-code', 'kubernetes', 'misconfiguration', 'security', 'security-tools', 'vulnerability', 'vulnerability-detection', 'vulnerability-scanners'] | ['containers', 'devsecops', 'docker', 'go', 'golang', 'iac', 'infrastructure-as-code', 'kubernetes', 'misconfiguration', 'security', 'security-tools', 'vulnerability', 'vulnerability-detection', 'vulnerability-scanners'] | 2024-01-12 | [('gefyrahq/gefyra', 0.6041578054428101, 'util', 3), ('pytest-dev/pytest-testinfra', 0.538640558719635, 'testing', 3), ('aswinnnn/pyscan', 0.5372655987739563, 'security', 4), ('tiiuae/sbomnix', 0.5336388945579529, 'util', 2), ('chaostoolkit/chaostoolkit', 0.5057849287986755, 'util', 0)] | 355 | 2 | null | 13.77 | 409 | 306 | 58 | 0 | 27 | 28 | 27 | 409 | 603 | 90 | 1.5 | 71 |
372 | ml-dl | https://github.com/pyg-team/pytorch_geometric | [] | null | [] | [] | null | null | null | pyg-team/pytorch_geometric | pytorch_geometric | 19,351 | 3,467 | 252 | Python | https://pyg.org | Graph Neural Network Library for PyTorch | pyg-team | 2024-01-14 | 2017-10-06 | 329 | 58.715648 | https://avatars.githubusercontent.com/u/89995122?v=4 | Graph Neural Network Library for PyTorch | ['deep-learning', 'geometric-deep-learning', 'graph-convolutional-networks', 'graph-neural-networks', 'pytorch'] | ['deep-learning', 'geometric-deep-learning', 'graph-convolutional-networks', 'graph-neural-networks', 'pytorch'] | 2024-01-13 | [('dmlc/dgl', 0.7811087965965271, 'ml-dl', 2), ('danielegrattarola/spektral', 0.7439136505126953, 'ml-dl', 2), ('pytorch/ignite', 0.7287918925285339, 'ml-dl', 2), ('hazyresearch/hgcn', 0.6979220509529114, 'ml', 0), ('mrdbourke/pytorch-deep-learning', 0.6894313097000122, 'study', 2), ('a-r-j/graphein', 0.6886248588562012, 'sim', 4), ('stellargraph/stellargraph', 0.6726529002189636, 'graph', 4), ('graphistry/pygraphistry', 0.6707996129989624, 'data', 0), ('skorch-dev/skorch', 0.6679598093032837, 'ml-dl', 1), ('chandlerbang/awesome-self-supervised-gnn', 0.6452118158340454, 'study', 2), ('rasbt/machine-learning-book', 0.6416996121406555, 'study', 2), ('intel/intel-extension-for-pytorch', 0.6297549605369568, 'perf', 2), ('rampasek/graphgps', 0.6243663430213928, 'graph', 0), ('denys88/rl_games', 0.618355929851532, 'ml-rl', 2), ('cvxgrp/pymde', 0.6165646910667419, 'ml', 1), ('tensorlayer/tensorlayer', 0.6017088294029236, 'ml-rl', 1), ('kornia/kornia', 0.5945971012115479, 'ml-dl', 2), ('facebookresearch/pytorch3d', 0.5885642766952515, 'ml-dl', 0), ('allenai/allennlp', 0.5823215246200562, 'nlp', 2), ('nicolas-chaulet/torch-points3d', 0.580845832824707, 'ml', 0), ('accenture/ampligraph', 0.58009934425354, 'data', 0), ('intellabs/bayesian-torch', 0.5782586932182312, 'ml', 2), ('pytorch/rl', 0.5780683755874634, 'ml-rl', 1), ('pytorch/torchrec', 0.570334255695343, 'ml-dl', 2), ('nvidia/apex', 0.5672152042388916, 'ml-dl', 0), ('rucaibox/recbole', 0.566724419593811, 'ml', 3), ('xl0/lovely-tensors', 0.5648797154426575, 'ml-dl', 2), ('benedekrozemberczki/tigerlily', 0.561957597732544, 'ml-dl', 1), ('keras-team/keras', 0.5601423978805542, 'ml-dl', 2), ('google-deepmind/materials_discovery', 0.5600719451904297, 'sim', 0), ('lucidrains/imagen-pytorch', 0.5598738193511963, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5547471046447754, 'ml-dl', 0), ('pytorch/data', 0.5495861768722534, 'data', 0), ('lutzroeder/netron', 0.5430858731269836, 'ml', 2), ('huggingface/transformers', 0.538887619972229, 'nlp', 2), ('karpathy/micrograd', 0.5318362712860107, 'study', 0), ('aistream-peelout/flow-forecast', 0.5282737016677856, 'time-series', 2), ('rentruewang/koila', 0.5282607674598694, 'ml', 2), ('neuralmagic/sparseml', 0.5272446274757385, 'ml-dl', 1), ('oml-team/open-metric-learning', 0.5263068079948425, 'ml', 2), ('horovod/horovod', 0.5256267189979553, 'ml-ops', 2), ('nvlabs/gcvit', 0.5232054591178894, 'diffusion', 1), ('huggingface/huggingface_hub', 0.5223245620727539, 'ml', 2), ('microsoft/deepspeed', 0.5219319462776184, 'ml-dl', 2), ('thu-ml/tianshou', 0.5205722451210022, 'ml-rl', 1), ('hysts/pytorch_image_classification', 0.5179129242897034, 'ml-dl', 1), ('explosion/thinc', 0.516636073589325, 'ml-dl', 2), ('tensorflow/tensorflow', 0.5166094899177551, 'ml-dl', 1), ('lightly-ai/lightly', 0.5151110887527466, 'ml', 2), ('ggerganov/ggml', 0.5148559212684631, 'ml', 0), ('huggingface/accelerate', 0.514308750629425, 'ml', 0), ('h4kor/graph-force', 0.5138907432556152, 'graph', 0), ('ageron/handson-ml2', 0.5134172439575195, 'ml', 0), ('google-research/deeplab2', 0.5118420720100403, 'ml', 0), ('ashleve/lightning-hydra-template', 0.5103349089622498, 'util', 2), ('arogozhnikov/einops', 0.5090392231941223, 'ml-dl', 2), ('mdbloice/augmentor', 0.5032522678375244, 'ml', 1), ('pytorch/pytorch', 0.503031313419342, 'ml-dl', 1), ('pygraphviz/pygraphviz', 0.502930760383606, 'viz', 0), ('pyro-ppl/pyro', 0.5015919208526611, 'ml-dl', 2), ('kevinmusgrave/pytorch-metric-learning', 0.501497745513916, 'ml', 2), ('uber/petastorm', 0.5014254450798035, 'data', 2)] | 477 | 6 | null | 20.87 | 535 | 427 | 76 | 0 | 3 | 6 | 3 | 535 | 785 | 90 | 1.5 | 71 |
599 | web | https://github.com/pyscript/pyscript | ['pyodide', 'cpython', 'wasm', 'webassembly'] | A framework that allows users to create rich Python applications in the browser using HTML's interface and the power of Pyodide, WASM, and modern web technologies. | [] | [] | null | null | null | pyscript/pyscript | pyscript | 17,260 | 1,434 | 167 | Python | https://pyscript.net/ | Try PyScript: https://pyscript.com Examples: https://tinyurl.com/pyscript-examples Community: https://discord.gg/HxvBtukrg2 | pyscript | 2024-01-14 | 2022-02-21 | 101 | 170.649718 | https://avatars.githubusercontent.com/u/100553281?v=4 | Try PyScript: https://pyscript.com Examples: https://tinyurl.com/pyscript-examples Community: https://discord.gg/HxvBtukrg2 | ['html', 'javascript', 'wasm'] | ['cpython', 'html', 'javascript', 'pyodide', 'wasm', 'webassembly'] | 2024-01-13 | [('masoniteframework/masonite', 0.6563617587089539, 'web', 0), ('pyscript/pyscript-cli', 0.606472909450531, 'web', 0), ('pywebio/pywebio', 0.5674092173576355, 'web', 0), ('bokeh/bokeh', 0.5267843008041382, 'viz', 1), ('killianlucas/open-interpreter', 0.5255423784255981, 'llm', 1), ('pyodide/pyodide', 0.5230824947357178, 'util', 3), ('microsoft/playwright-python', 0.5149538516998291, 'testing', 0), ('r0x0r/pywebview', 0.5112079381942749, 'gui', 2)] | 116 | 1 | null | 6.25 | 181 | 166 | 23 | 0 | 6 | 5 | 6 | 181 | 340 | 90 | 1.9 | 71 |
888 | diffusion | https://github.com/apple/ml-stable-diffusion | [] | null | [] | [] | null | null | null | apple/ml-stable-diffusion | ml-stable-diffusion | 15,566 | 835 | 134 | Python | null | Stable Diffusion with Core ML on Apple Silicon | apple | 2024-01-14 | 2022-11-16 | 62 | 247.640909 | https://avatars.githubusercontent.com/u/10639145?v=4 | Stable Diffusion with Core ML on Apple Silicon | [] | [] | 2023-11-14 | [('divamgupta/diffusionbee-stable-diffusion-ui', 0.5508177876472473, 'diffusion', 0), ('ml-explore/mlx', 0.5221449136734009, 'ml', 0), ('divamgupta/stable-diffusion-tensorflow', 0.5180650949478149, 'diffusion', 0), ('carson-katri/dream-textures', 0.5164445042610168, 'diffusion', 0)] | 31 | 4 | null | 1.37 | 40 | 17 | 14 | 2 | 5 | 5 | 5 | 40 | 104 | 90 | 2.6 | 71 |
39 | jupyter | https://github.com/jupyterlab/jupyterlab | [] | null | [] | [] | null | null | null | jupyterlab/jupyterlab | jupyterlab | 13,540 | 2,973 | 315 | TypeScript | https://jupyterlab.readthedocs.io/ | JupyterLab computational environment. | jupyterlab | 2024-01-14 | 2016-06-03 | 399 | 33.886307 | https://avatars.githubusercontent.com/u/22800682?v=4 | JupyterLab computational environment. | ['jupyter', 'jupyterlab'] | ['jupyter', 'jupyterlab'] | 2024-01-13 | [('jupyterlab/jupyterlab-desktop', 0.7525447607040405, 'jupyter', 2), ('ipython/ipyparallel', 0.6818181872367859, 'perf', 1), ('jupyter/notebook', 0.669508159160614, 'jupyter', 1), ('ipython/ipykernel', 0.662561297416687, 'util', 1), ('jupyter/nbformat', 0.6569828987121582, 'jupyter', 0), ('jupyterlite/jupyterlite', 0.6288254261016846, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.6188204884529114, 'jupyter', 0), ('mamba-org/gator', 0.6041745543479919, 'jupyter', 0), ('jupyter/nbconvert', 0.5970379710197449, 'jupyter', 0), ('vizzuhq/ipyvizzu', 0.5963035821914673, 'jupyter', 1), ('jupyter-lsp/jupyterlab-lsp', 0.5912031531333923, 'jupyter', 2), ('mwouts/jupytext', 0.5835863947868347, 'jupyter', 1), ('chaoleili/jupyterlab_tensorboard', 0.5774864554405212, 'jupyter', 1), ('jakevdp/pythondatasciencehandbook', 0.5746160745620728, 'study', 0), ('jupyterlab/jupyter-ai', 0.5743774771690369, 'jupyter', 2), ('voila-dashboards/voila', 0.5699175596237183, 'jupyter', 1), ('koaning/drawdata', 0.569868266582489, 'jupyter', 1), ('maartenbreddels/ipyvolume', 0.5636622309684753, 'jupyter', 1), ('quantopian/qgrid', 0.5634688138961792, 'jupyter', 0), ('nteract/testbook', 0.5517867207527161, 'jupyter', 0), ('computationalmodelling/nbval', 0.5462405681610107, 'jupyter', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5447031259536743, 'study', 0), ('cohere-ai/notebooks', 0.5374837517738342, 'llm', 0), ('jupyter-widgets/ipyleaflet', 0.523621678352356, 'gis', 1), ('aws/graph-notebook', 0.5233699083328247, 'jupyter', 1), ('bloomberg/ipydatagrid', 0.518395185470581, 'jupyter', 0), ('ageron/handson-ml2', 0.5005123019218445, 'ml', 0)] | 577 | 8 | null | 22.79 | 1,042 | 801 | 93 | 0 | 35 | 4,883 | 35 | 1,042 | 1,691 | 90 | 1.6 | 71 |
1,560 | ml | https://github.com/ggerganov/ggml | [] | null | [] | [] | null | null | null | ggerganov/ggml | ggml | 8,536 | 822 | 109 | C | null | Tensor library for machine learning | ggerganov | 2024-01-14 | 2022-09-18 | 71 | 119.743487 | null | Tensor library for machine learning | ['automatic-differentiation', 'large-language-models', 'machine-learning', 'tensor-algebra'] | ['automatic-differentiation', 'large-language-models', 'machine-learning', 'tensor-algebra'] | 2024-01-13 | [('tensorly/tensorly', 0.7053402066230774, 'ml-dl', 2), ('arogozhnikov/einops', 0.674818754196167, 'ml-dl', 0), ('xl0/lovely-tensors', 0.6742641925811768, 'ml-dl', 0), ('rafiqhasan/auto-tensorflow', 0.6585282683372498, 'ml-dl', 1), ('pytorch/pytorch', 0.6398614645004272, 'ml-dl', 1), ('nvidia/tensorrt-llm', 0.6161227822303772, 'viz', 0), ('google/tf-quant-finance', 0.6140791773796082, 'finance', 0), ('keras-team/autokeras', 0.6085128784179688, 'ml-dl', 1), ('tensorflow/tensorflow', 0.6057413816452026, 'ml-dl', 1), ('karpathy/micrograd', 0.6055065393447876, 'study', 0), ('pytorch/ignite', 0.6042031645774841, 'ml-dl', 1), ('huggingface/transformers', 0.6029016375541687, 'nlp', 1), ('skorch-dev/skorch', 0.5978483557701111, 'ml-dl', 1), ('tensorflow/similarity', 0.5696033239364624, 'ml-dl', 1), ('patrick-kidger/torchtyping', 0.5691167712211609, 'typing', 0), ('horovod/horovod', 0.5658283829689026, 'ml-ops', 1), ('ageron/handson-ml2', 0.5649846196174622, 'ml', 0), ('intel/intel-extension-for-pytorch', 0.5619326233863831, 'perf', 1), ('aws/sagemaker-python-sdk', 0.5583137273788452, 'ml', 1), ('d2l-ai/d2l-en', 0.5564393997192383, 'study', 1), ('rasbt/machine-learning-book', 0.5550714135169983, 'study', 1), ('tensorflow/mesh', 0.5549049973487854, 'ml-dl', 0), ('tensorlayer/tensorlayer', 0.548178493976593, 'ml-rl', 0), ('neuralmagic/sparseml', 0.5481603741645813, 'ml-dl', 0), ('rasbt/mlxtend', 0.5479773283004761, 'ml', 1), ('oml-team/open-metric-learning', 0.5477278232574463, 'ml', 0), ('huggingface/exporters', 0.5472779870033264, 'ml', 1), ('microsoft/flaml', 0.5470587611198425, 'ml', 1), ('uber/petastorm', 0.5469512939453125, 'data', 1), ('mrdbourke/pytorch-deep-learning', 0.5461394190788269, 'study', 1), ('microsoft/nni', 0.5407408475875854, 'ml', 1), ('huggingface/datasets', 0.5396940112113953, 'nlp', 1), ('probml/pyprobml', 0.536136269569397, 'ml', 1), ('lightly-ai/lightly', 0.5310502052307129, 'ml', 1), ('explosion/thinc', 0.5289695858955383, 'ml-dl', 1), ('nvidia/deeplearningexamples', 0.5287749171257019, 'ml-dl', 1), ('tensorflow/data-validation', 0.525627076625824, 'ml-ops', 0), ('tensorflow/addons', 0.525490939617157, 'ml', 1), ('hannibal046/awesome-llm', 0.5245451927185059, 'study', 0), ('timdettmers/bitsandbytes', 0.5234319567680359, 'util', 0), ('huggingface/huggingface_hub', 0.5206968188285828, 'ml', 1), ('tensorflow/tensor2tensor', 0.519944965839386, 'ml', 1), ('pycaret/pycaret', 0.5191986560821533, 'ml', 1), ('scikit-learn-contrib/lightning', 0.5173808336257935, 'ml', 1), ('keras-team/keras-nlp', 0.5159798860549927, 'nlp', 1), ('pyg-team/pytorch_geometric', 0.5148559212684631, 'ml-dl', 0), ('nccr-itmo/fedot', 0.5140013098716736, 'ml-ops', 1), ('huggingface/evaluate', 0.5103128552436829, 'ml', 1), ('keras-rl/keras-rl', 0.5087230205535889, 'ml-rl', 1), ('optimalscale/lmflow', 0.5078336596488953, 'llm', 0), ('determined-ai/determined', 0.5071011185646057, 'ml-ops', 1), ('microsoft/lora', 0.5070888996124268, 'llm', 0), ('keras-team/keras', 0.5067704319953918, 'ml-dl', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5067695379257202, 'study', 0), ('ray-project/ray', 0.505761981010437, 'ml-ops', 1), ('rasbt/deeplearning-models', 0.5030370354652405, 'ml-dl', 0), ('pytorch/rl', 0.5019291043281555, 'ml-rl', 1)] | 112 | 7 | null | 9.9 | 129 | 85 | 16 | 0 | 0 | 0 | 0 | 129 | 422 | 90 | 3.3 | 71 |
1,196 | llm | https://github.com/mlc-ai/web-llm | [] | null | [] | [] | null | null | null | mlc-ai/web-llm | web-llm | 8,186 | 493 | 92 | TypeScript | https://mlc.ai/web-llm | Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support. | mlc-ai | 2024-01-13 | 2023-04-13 | 41 | 196.239726 | https://avatars.githubusercontent.com/u/106173866?v=4 | Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support. | ['chatgpt', 'deep-learning', 'language-model', 'llm', 'tvm', 'webgpu', 'webml'] | ['chatgpt', 'deep-learning', 'language-model', 'llm', 'tvm', 'webgpu', 'webml'] | 2024-01-04 | [('mlc-ai/web-stable-diffusion', 0.6759905219078064, 'diffusion', 4), ('microsoft/autogen', 0.661967396736145, 'llm', 1), ('next-gpt/next-gpt', 0.6524577140808105, 'llm', 2), ('nomic-ai/gpt4all', 0.6522467136383057, 'llm', 1), ('hwchase17/langchain', 0.6466255187988281, 'llm', 1), ('young-geng/easylm', 0.6428095102310181, 'llm', 2), ('thudm/chatglm2-6b', 0.6331812143325806, 'llm', 1), ('oobabooga/text-generation-webui', 0.6323723793029785, 'llm', 1), ('bigscience-workshop/petals', 0.6224874258041382, 'data', 1), ('lm-sys/fastchat', 0.6169783473014832, 'llm', 1), ('embedchain/embedchain', 0.6080430746078491, 'llm', 2), ('killianlucas/open-interpreter', 0.6023691892623901, 'llm', 1), ('run-llama/rags', 0.5972565412521362, 'llm', 2), ('fasteval/fasteval', 0.5912193655967712, 'llm', 1), ('nat/openplayground', 0.589094340801239, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5826047658920288, 'perf', 0), ('xtekky/gpt4free', 0.5752508640289307, 'llm', 2), ('openlmlab/moss', 0.5738821029663086, 'llm', 3), ('lianjiatech/belle', 0.5615787506103516, 'llm', 0), ('encode/starlette', 0.5606010556221008, 'web', 0), ('salesforce/xgen', 0.5496227741241455, 'llm', 2), ('guidance-ai/guidance', 0.5491284728050232, 'llm', 2), ('titanml/takeoff', 0.548348069190979, 'llm', 2), ('hannibal046/awesome-llm', 0.5478937029838562, 'study', 1), ('hiyouga/llama-factory', 0.5438234210014343, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5438233613967896, 'llm', 2), ('alphasecio/langchain-examples', 0.5424495339393616, 'llm', 1), ('li-plus/chatglm.cpp', 0.542007565498352, 'llm', 0), ('bobazooba/xllm', 0.5402325987815857, 'llm', 3), ('blinkdl/chatrwkv', 0.5393033623695374, 'llm', 2), ('sjtu-ipads/powerinfer', 0.5370975136756897, 'llm', 1), ('dylanhogg/llmgraph', 0.5363897085189819, 'ml', 2), ('shishirpatil/gorilla', 0.533381462097168, 'llm', 2), ('pathwaycom/llm-app', 0.5320335030555725, 'llm', 1), ('deepset-ai/haystack', 0.5301832556724548, 'llm', 2), ('langchain-ai/langgraph', 0.5244644284248352, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5234134197235107, 'llm', 1), ('langchain-ai/chat-langchain', 0.5200137495994568, 'llm', 0), ('pallets/werkzeug', 0.5196402668952942, 'web', 0), ('ctlllll/llm-toolmaker', 0.5185114145278931, 'llm', 1), ('freedomintelligence/llmzoo', 0.517315149307251, 'llm', 1), ('rasahq/rasa', 0.5135403275489807, 'llm', 0), ('aiqc/aiqc', 0.5105668306350708, 'ml-ops', 0), ('lightning-ai/lit-llama', 0.508145809173584, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5051769614219666, 'llm', 2), ('databrickslabs/dolly', 0.5030844807624817, 'llm', 0), ('explosion/spacy-llm', 0.5018036961555481, 'llm', 1), ('mayooear/gpt4-pdf-chatbot-langchain', 0.50135737657547, 'llm', 0), ('deeppavlov/deeppavlov', 0.5006988644599915, 'nlp', 1), ('baichuan-inc/baichuan-13b', 0.5006130933761597, 'llm', 1), ('lucidrains/toolformer-pytorch', 0.5002791881561279, 'llm', 2)] | 25 | 8 | null | 2.58 | 75 | 61 | 9 | 0 | 1 | 1 | 1 | 75 | 174 | 90 | 2.3 | 71 |
1,712 | ml-ops | https://github.com/bentoml/openllm | [] | null | [] | [] | null | null | null | bentoml/openllm | OpenLLM | 7,553 | 519 | 49 | Python | https://bentoml.com | Operating LLMs in production | bentoml | 2024-01-14 | 2023-04-19 | 40 | 184.863636 | https://avatars.githubusercontent.com/u/49176046?v=4 | Operating LLMs in production | ['ai', 'bentoml', 'falcon', 'fine-tuning', 'llama', 'llama2', 'llm', 'llm-inference', 'llm-ops', 'llm-serving', 'llmops', 'mistral', 'ml', 'mlops', 'model-inference', 'mpt', 'open-source-llm', 'openllm', 'stablelm', 'vicuna'] | ['ai', 'bentoml', 'falcon', 'fine-tuning', 'llama', 'llama2', 'llm', 'llm-inference', 'llm-ops', 'llm-serving', 'llmops', 'mistral', 'ml', 'mlops', 'model-inference', 'mpt', 'open-source-llm', 'openllm', 'stablelm', 'vicuna'] | 2024-01-12 | [('vllm-project/vllm', 0.7688142657279968, 'llm', 5), ('predibase/lorax', 0.7207032442092896, 'llm', 6), ('eugeneyan/open-llms', 0.7019832134246826, 'study', 1), ('bigscience-workshop/petals', 0.6789776682853699, 'data', 3), ('ray-project/ray-llm', 0.6621026396751404, 'llm', 4), ('h2oai/h2o-llmstudio', 0.6586171388626099, 'llm', 5), ('tigerlab-ai/tiger', 0.6545884013175964, 'llm', 2), ('alpha-vllm/llama2-accessory', 0.6482536792755127, 'llm', 1), ('hiyouga/llama-factory', 0.6292675733566284, 'llm', 4), ('hiyouga/llama-efficient-tuning', 0.6292673945426941, 'llm', 4), ('agenta-ai/agenta', 0.6264759302139282, 'llm', 2), ('microsoft/promptflow', 0.6225191950798035, 'llm', 2), ('ray-project/llm-applications', 0.6087220311164856, 'llm', 2), ('microsoft/torchscale', 0.5949733853340149, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5912082195281982, 'perf', 1), ('jerryjliu/llama_index', 0.5906221866607666, 'llm', 3), ('bobazooba/xllm', 0.5858603119850159, 'llm', 5), ('truera/trulens', 0.5837077498435974, 'llm', 2), ('ludwig-ai/ludwig', 0.5829933881759644, 'ml-ops', 6), ('microsoft/lmops', 0.581097424030304, 'llm', 1), ('confident-ai/deepeval', 0.575341522693634, 'testing', 2), ('tairov/llama2.mojo', 0.5740443468093872, 'llm', 2), ('pathwaycom/llm-app', 0.5679009556770325, 'llm', 2), ('hegelai/prompttools', 0.565089225769043, 'llm', 0), ('microsoft/semantic-kernel', 0.5633988380432129, 'llm', 2), ('titanml/takeoff', 0.5552429556846619, 'llm', 2), ('bentoml/bentoml', 0.5529214143753052, 'ml-ops', 5), ('young-geng/easylm', 0.5489903688430786, 'llm', 1), ('salesforce/xgen', 0.5479778051376343, 'llm', 1), ('microsoft/jarvis', 0.5471473336219788, 'llm', 0), ('openai/evals', 0.5440770387649536, 'llm', 0), ('deepset-ai/haystack', 0.543747067451477, 'llm', 1), ('argilla-io/argilla', 0.5431055426597595, 'nlp', 3), ('nomic-ai/gpt4all', 0.5412029027938843, 'llm', 1), ('run-llama/llama-hub', 0.5397924184799194, 'data', 1), ('lightning-ai/lit-gpt', 0.5373291373252869, 'llm', 1), ('skypilot-org/skypilot', 0.536402702331543, 'llm', 1), ('run-llama/llama-lab', 0.5358179211616516, 'llm', 1), ('iryna-kondr/scikit-llm', 0.5351253151893616, 'llm', 1), ('nebuly-ai/nebullvm', 0.5305408835411072, 'perf', 2), ('citadel-ai/langcheck', 0.5283021926879883, 'llm', 0), ('salesforce/codet5', 0.5279268622398376, 'nlp', 0), ('tloen/alpaca-lora', 0.5242617726325989, 'llm', 1), ('zrrskywalker/llama-adapter', 0.5195848345756531, 'llm', 1), ('microsoft/llama-2-onnx', 0.5186194181442261, 'llm', 1), ('mooler0410/llmspracticalguide', 0.516433596611023, 'study', 0), ('ajndkr/lanarky', 0.5158595442771912, 'llm', 1), ('berriai/litellm', 0.5140005350112915, 'llm', 2), ('polyaxon/polyaxon', 0.5105753540992737, 'ml-ops', 2), ('explosion/spacy-llm', 0.5071743726730347, 'llm', 3), ('shishirpatil/gorilla', 0.5051870942115784, 'llm', 1), ('determined-ai/determined', 0.5048798322677612, 'ml-ops', 1), ('microsoft/llmlingua', 0.5037171244621277, 'llm', 0), ('zilliztech/gptcache', 0.5029482245445251, 'llm', 2)] | 23 | 2 | null | 26.02 | 385 | 341 | 9 | 0 | 105 | 184 | 105 | 384 | 275 | 90 | 0.7 | 71 |
1,464 | llm | https://github.com/huggingface/text-generation-inference | [] | null | [] | [] | null | null | null | huggingface/text-generation-inference | text-generation-inference | 6,605 | 714 | 88 | Python | http://hf.co/docs/text-generation-inference | Large Language Model Text Generation Inference | huggingface | 2024-01-14 | 2022-10-08 | 68 | 96.524008 | https://avatars.githubusercontent.com/u/25720743?v=4 | Large Language Model Text Generation Inference | ['bloom', 'deep-learning', 'falcon', 'gpt', 'inference', 'nlp', 'pytorch', 'starcoder', 'transformer'] | ['bloom', 'deep-learning', 'falcon', 'gpt', 'inference', 'nlp', 'pytorch', 'starcoder', 'transformer'] | 2024-01-11 | [('infinitylogesh/mutate', 0.6840097904205322, 'nlp', 0), ('lianjiatech/belle', 0.6746523380279541, 'llm', 1), ('bytedance/lightseq', 0.672805666923523, 'nlp', 3), ('google-research/electra', 0.648766815662384, 'ml-dl', 2), ('minimaxir/gpt-2-simple', 0.6420865058898926, 'llm', 0), ('minimaxir/textgenrnn', 0.6332951188087463, 'nlp', 1), ('hannibal046/awesome-llm', 0.616241455078125, 'study', 1), ('google/sentencepiece', 0.607265830039978, 'nlp', 0), ('optimalscale/lmflow', 0.6065784692764282, 'llm', 3), ('princeton-nlp/alce', 0.6029461622238159, 'llm', 0), ('squeezeailab/squeezellm', 0.6000766158103943, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5956083536148071, 'llm', 1), ('bigcode-project/starcoder', 0.5950606465339661, 'llm', 0), ('databrickslabs/dolly', 0.5939000248908997, 'llm', 1), ('yueyu1030/attrprompt', 0.5905746221542358, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.5844063758850098, 'llm', 1), ('sharonzhou/long_stable_diffusion', 0.5840281844139099, 'diffusion', 0), ('bigscience-workshop/megatron-deepspeed', 0.5798518061637878, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5798518061637878, 'llm', 0), ('togethercomputer/redpajama-data', 0.5783564448356628, 'llm', 0), ('deepset-ai/farm', 0.5736597180366516, 'nlp', 3), ('explosion/spacy-llm', 0.5718468427658081, 'llm', 2), ('allenai/allennlp', 0.5714684128761292, 'nlp', 3), ('jonasgeiping/cramming', 0.5711867213249207, 'nlp', 0), ('openlmlab/moss', 0.5647656917572021, 'llm', 1), ('microsoft/autogen', 0.5635223984718323, 'llm', 1), ('minimaxir/aitextgen', 0.563347339630127, 'llm', 0), ('ai21labs/lm-evaluation', 0.5604375004768372, 'llm', 0), ('huggingface/transformers', 0.557208240032196, 'nlp', 4), ('ctlllll/llm-toolmaker', 0.5557337403297424, 'llm', 0), ('salesforce/xgen', 0.5519874691963196, 'llm', 1), ('next-gpt/next-gpt', 0.5511967539787292, 'llm', 0), ('bobazooba/xllm', 0.5498690605163574, 'llm', 3), ('alibaba/easynlp', 0.5467448234558105, 'nlp', 3), ('baichuan-inc/baichuan-13b', 0.546048104763031, 'llm', 0), ('pytorch-labs/gpt-fast', 0.5448298454284668, 'llm', 2), ('facebookresearch/shepherd', 0.5433861017227173, 'llm', 0), ('cg123/mergekit', 0.541591465473175, 'llm', 0), ('llmware-ai/llmware', 0.5404112339019775, 'llm', 2), ('lm-sys/fastchat', 0.538799524307251, 'llm', 0), ('microsoft/lora', 0.5352991223335266, 'llm', 2), ('intellabs/fastrag', 0.5351554155349731, 'nlp', 1), ('bigscience-workshop/biomedical', 0.5347291231155396, 'data', 0), ('norskregnesentral/skweak', 0.5326890349388123, 'nlp', 0), ('paddlepaddle/paddlenlp', 0.531993567943573, 'llm', 1), ('lupantech/chameleon-llm', 0.531190812587738, 'llm', 0), ('maartengr/bertopic', 0.5277509093284607, 'nlp', 1), ('eugeneyan/obsidian-copilot', 0.5260320901870728, 'llm', 0), ('juncongmoo/pyllama', 0.5241082310676575, 'llm', 0), ('lvwerra/trl', 0.523781955242157, 'llm', 0), ('freedomintelligence/llmzoo', 0.523625373840332, 'llm', 0), ('mit-han-lab/streaming-llm', 0.5219200253486633, 'llm', 0), ('vllm-project/vllm', 0.5211599469184875, 'llm', 4), ('muennighoff/sgpt', 0.519349992275238, 'llm', 1), ('reasoning-machines/pal', 0.5183734893798828, 'llm', 0), ('huggingface/text-embeddings-inference', 0.5171723365783691, 'llm', 0), ('nvidia/deeplearningexamples', 0.5152902007102966, 'ml-dl', 3), ('openai/finetune-transformer-lm', 0.5149126648902893, 'llm', 0), ('graykode/nlp-tutorial', 0.5133894681930542, 'study', 3), ('nltk/nltk', 0.5107032060623169, 'nlp', 1), ('srush/minichain', 0.5085004568099976, 'llm', 0), ('microsoft/unilm', 0.5068984627723694, 'nlp', 1), ('eleutherai/the-pile', 0.5064693093299866, 'data', 0), ('thudm/cogvideo', 0.5058658719062805, 'ml', 0), ('facebookresearch/seamless_communication', 0.5040040612220764, 'nlp', 0), ('keras-team/keras-nlp', 0.5031775236129761, 'nlp', 2), ('bigscience-workshop/petals', 0.5030701160430908, 'data', 7), ('extreme-bert/extreme-bert', 0.5023447871208191, 'llm', 4), ('openbmb/toolbench', 0.5014093518257141, 'llm', 0)] | 59 | 4 | null | 9.02 | 365 | 244 | 15 | 0 | 32 | 26 | 32 | 365 | 867 | 90 | 2.4 | 71 |
1,848 | llm | https://github.com/assafelovic/gpt-researcher | ['researcher', 'autonomous-agent'] | null | [] | [] | null | null | null | assafelovic/gpt-researcher | gpt-researcher | 6,496 | 770 | 70 | Python | https://tavily.com | GPT based autonomous agent that does online comprehensive research on any given topic | assafelovic | 2024-01-14 | 2023-05-12 | 37 | 172.897338 | null | GPT based autonomous agent that does online comprehensive research on any given topic | [] | ['autonomous-agent', 'researcher'] | 2024-01-07 | [('yoheinakajima/babyagi', 0.6752115488052368, 'llm', 0), ('linksoul-ai/autoagents', 0.6728865504264832, 'llm', 0), ('torantulino/auto-gpt', 0.6427838802337646, 'llm', 0), ('geekan/metagpt', 0.6312734484672546, 'llm', 0), ('transformeroptimus/superagi', 0.5870476961135864, 'llm', 0), ('oneil512/insight', 0.5495372414588928, 'ml', 0), ('google-research/google-research', 0.545631468296051, 'ml', 0), ('operand/agency', 0.5227841734886169, 'llm', 1), ('langchain-ai/opengpts', 0.511093020439148, 'llm', 0), ('antonosika/gpt-engineer', 0.5011528730392456, 'llm', 1)] | 25 | 5 | null | 6.81 | 121 | 88 | 8 | 0 | 13 | 20 | 13 | 120 | 139 | 90 | 1.2 | 71 |
178 | web | https://github.com/psf/requests | [] | null | [] | [] | null | null | null | psf/requests | requests | 50,848 | 9,298 | 1,340 | Python | https://requests.readthedocs.io/en/latest/ | A simple, yet elegant, HTTP library. | psf | 2024-01-14 | 2011-02-13 | 676 | 75.187157 | https://avatars.githubusercontent.com/u/50630501?v=4 | A simple, yet elegant, HTTP library. | ['client', 'cookies', 'forhumans', 'http', 'humans', 'python-requests', 'requests'] | ['client', 'cookies', 'forhumans', 'http', 'humans', 'python-requests', 'requests'] | 2024-01-08 | [('requests/toolbelt', 0.7315183281898499, 'util', 2), ('encode/httpx', 0.7030969858169556, 'web', 1), ('encode/uvicorn', 0.6152986884117126, 'web', 1), ('getsentry/responses', 0.6119535565376282, 'testing', 1), ('simple-salesforce/simple-salesforce', 0.5815314650535583, 'data', 0), ('hugapi/hug', 0.5775818228721619, 'util', 1), ('cherrypy/cherrypy', 0.5770725607872009, 'web', 1), ('scrapy/scrapy', 0.5722671151161194, 'data', 0), ('falconry/falcon', 0.5613847970962524, 'web', 1), ('pallets/werkzeug', 0.559667706489563, 'web', 1), ('magicstack/httptools', 0.5530205965042114, 'web', 0), ('googleapis/google-api-python-client', 0.552095353603363, 'util', 0), ('neoteroi/blacksheep', 0.551236629486084, 'web', 1), ('roniemartinez/dude', 0.5494452118873596, 'util', 0), ('dsdanielpark/bard-api', 0.5480201244354248, 'llm', 0), ('pallets/quart', 0.5377407670021057, 'web', 0), ('binux/pyspider', 0.5332942605018616, 'data', 0), ('aio-libs/aiohttp', 0.5318570137023926, 'web', 1), ('jiffyclub/snakeviz', 0.5308777093887329, 'profiling', 0), ('alirezamika/autoscraper', 0.5295840501785278, 'data', 0), ('tedivm/robs_awesome_python_template', 0.5218177437782288, 'template', 0), ('snyk-labs/pysnyk', 0.518162727355957, 'security', 0), ('masoniteframework/masonite', 0.5165953040122986, 'web', 0), ('klen/muffin', 0.5109789967536926, 'web', 0), ('lyz-code/cookiecutter-python-project', 0.5095129013061523, 'template', 0), ('nv7-github/googlesearch', 0.5044116973876953, 'util', 0), ('webpy/webpy', 0.5032954812049866, 'web', 0)] | 748 | 7 | null | 1.27 | 148 | 115 | 157 | 0 | 3 | 12 | 3 | 148 | 152 | 90 | 1 | 70 |
261 | web | https://github.com/sherlock-project/sherlock | [] | null | [] | [] | null | null | null | sherlock-project/sherlock | sherlock | 46,128 | 5,887 | 1,063 | Python | http://sherlock-project.github.io | π Hunt down social media accounts by username across social networks | sherlock-project | 2024-01-14 | 2018-12-24 | 266 | 173.320451 | https://avatars.githubusercontent.com/u/48293496?v=4 | π Hunt down social media accounts by username across social networks | ['cli', 'information-gathering', 'linux', 'macos', 'osint', 'reconnaissance', 'redteam', 'sherlock', 'tools', 'windows'] | ['cli', 'information-gathering', 'linux', 'macos', 'osint', 'reconnaissance', 'redteam', 'sherlock', 'tools', 'windows'] | 2024-01-10 | [('twintproject/twint', 0.5957009196281433, 'data', 1)] | 225 | 4 | null | 2.71 | 78 | 51 | 62 | 0 | 0 | 0 | 0 | 78 | 62 | 90 | 0.8 | 70 |
220 | util | https://github.com/pyenv/pyenv | ['pip', 'venv'] | pyenv lets you easily switch between multiple versions of Python. | [] | [] | null | null | null | pyenv/pyenv | pyenv | 34,980 | 2,948 | 386 | Roff | null | Simple Python version management | pyenv | 2024-01-14 | 2012-08-31 | 595 | 58.733509 | https://avatars.githubusercontent.com/u/16530698?v=4 | Simple Python version management | ['shell'] | ['pip', 'shell', 'venv'] | 2023-12-31 | [('pypa/pipenv', 0.6903738379478455, 'util', 2), ('pypa/hatch', 0.6283936500549316, 'util', 0), ('pypa/virtualenv', 0.6280038952827454, 'util', 2), ('pypa/pipx', 0.6269603371620178, 'util', 2), ('pomponchik/instld', 0.6027212738990784, 'util', 2), ('thoth-station/micropipenv', 0.5758981704711914, 'util', 1), ('pantsbuild/pex', 0.5503339171409607, 'util', 1), ('pdm-project/pdm', 0.5091418027877808, 'util', 0)] | 437 | 5 | null | 3.21 | 86 | 70 | 138 | 0 | 25 | 14 | 25 | 86 | 163 | 90 | 1.9 | 70 |
954 | security | https://github.com/certbot/certbot | [] | null | [] | [] | null | null | null | certbot/certbot | certbot | 30,525 | 3,449 | 761 | Python | null | Certbot is EFF's tool to obtain certs from Let's Encrypt and (optionally) auto-enable HTTPS on your server. It can also act as a client for any other CA that uses the ACME protocol. | certbot | 2024-01-14 | 2014-11-12 | 480 | 63.480392 | https://avatars.githubusercontent.com/u/17889013?v=4 | Certbot is EFF's tool to obtain certs from Let's Encrypt and (optionally) auto-enable HTTPS on your server. It can also act as a client for any other CA that uses the ACME protocol. | ['acme', 'acme-client', 'certbot', 'certificate', 'letsencrypt'] | ['acme', 'acme-client', 'certbot', 'certificate', 'letsencrypt'] | 2024-01-06 | [] | 525 | 4 | null | 4.79 | 137 | 79 | 112 | 0 | 10 | 14 | 10 | 138 | 214 | 90 | 1.6 | 70 |
17 | nlp | https://github.com/explosion/spacy | [] | null | [] | [] | null | null | null | explosion/spacy | spaCy | 27,972 | 4,354 | 557 | Python | https://spacy.io | π« Industrial-strength Natural Language Processing (NLP) in Python | explosion | 2024-01-14 | 2014-07-03 | 499 | 55.975986 | https://avatars.githubusercontent.com/u/20011530?v=4 | π« Industrial-strength Natural Language Processing (NLP) in Python | ['ai', 'artificial-intelligence', 'cython', 'data-science', 'deep-learning', 'entity-linking', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'neural-network', 'neural-networks', 'nlp', 'nlp-library', 'spacy', 'text-classification', 'tokenization'] | ['ai', 'artificial-intelligence', 'cython', 'data-science', 'deep-learning', 'entity-linking', 'machine-learning', 'named-entity-recognition', 'natural-language-processing', 'neural-network', 'neural-networks', 'nlp', 'nlp-library', 'spacy', 'text-classification', 'tokenization'] | 2024-01-02 | [('sloria/textblob', 0.7043011784553528, 'nlp', 2), ('nltk/nltk', 0.6628869771957397, 'nlp', 3), ('flairnlp/flair', 0.6546562910079956, 'nlp', 4), ('allenai/allennlp', 0.6516764163970947, 'nlp', 4), ('keras-team/keras-nlp', 0.6470063924789429, 'nlp', 4), ('explosion/spacy-models', 0.6409233212471008, 'nlp', 4), ('norskregnesentral/skweak', 0.6230126619338989, 'nlp', 4), ('rasahq/rasa', 0.6100810170173645, 'llm', 4), ('huggingface/transformers', 0.6091046929359436, 'nlp', 5), ('deepset-ai/farm', 0.6052958965301514, 'nlp', 3), ('alibaba/easynlp', 0.6040478348731995, 'nlp', 4), ('pemistahl/lingua-py', 0.5869116187095642, 'nlp', 2), ('paddlepaddle/paddlenlp', 0.5861974954605103, 'llm', 1), ('makcedward/nlpaug', 0.5835755467414856, 'nlp', 6), ('explosion/thinc', 0.5825142860412598, 'ml-dl', 7), ('explosion/spacy-llm', 0.573280930519104, 'llm', 6), ('lexpredict/lexpredict-lexnlp', 0.5584388971328735, 'nlp', 1), ('thilinarajapakse/simpletransformers', 0.5573221445083618, 'nlp', 2), ('llmware-ai/llmware', 0.5547406077384949, 'llm', 3), ('ddbourgin/numpy-ml', 0.5528154373168945, 'ml', 2), ('clips/pattern', 0.5512140989303589, 'nlp', 2), ('nvidia/deeplearningexamples', 0.5494264364242554, 'ml-dl', 2), ('graykode/nlp-tutorial', 0.5477665066719055, 'study', 2), ('dylanhogg/awesome-python', 0.5455989241600037, 'study', 5), ('nvidia/nemo', 0.541452169418335, 'nlp', 3), ('gradio-app/gradio', 0.5368600487709045, 'viz', 3), ('lukaszahradnik/pyneuralogic', 0.5333031415939331, 'math', 2), ('merantix-momentum/squirrel-core', 0.5305957198143005, 'ml', 6), ('franck-dernoncourt/neuroner', 0.527627170085907, 'nlp', 5), ('minimaxir/aitextgen', 0.5253174901008606, 'llm', 0), ('huggingface/datasets', 0.5209731459617615, 'nlp', 4), ('lucidrains/toolformer-pytorch', 0.5190293192863464, 'llm', 2), ('explosion/spacy-stanza', 0.5188982486724854, 'nlp', 5), ('explosion/spacy-transformers', 0.5188299417495728, 'llm', 4), ('tensorly/tensorly', 0.5184281468391418, 'ml-dl', 1), ('jalammar/ecco', 0.5182880163192749, 'ml-interpretability', 2), ('fastai/fastcore', 0.5157615542411804, 'util', 0), ('ibm/transition-amr-parser', 0.5131350159645081, 'nlp', 2), ('databrickslabs/dolly', 0.5090692043304443, 'llm', 0), ('huggingface/neuralcoref', 0.5070719122886658, 'nlp', 4), ('kagisearch/vectordb', 0.506615936756134, 'data', 3), ('deeppavlov/deeppavlov', 0.5052632689476013, 'nlp', 6), ('scikit-learn/scikit-learn', 0.5003823637962341, 'ml', 2), ('quantconnect/lean', 0.5002435445785522, 'finance', 0)] | 746 | 3 | null | 6.94 | 97 | 76 | 116 | 0 | 12 | 16 | 12 | 97 | 177 | 90 | 1.8 | 70 |
1,064 | diffusion | https://github.com/lllyasviel/controlnet | [] | null | [] | [] | null | null | null | lllyasviel/controlnet | ControlNet | 26,084 | 2,427 | 202 | Python | null | Let us control diffusion models! | lllyasviel | 2024-01-14 | 2023-02-01 | 51 | 502.997245 | null | Let us control diffusion models! | [] | [] | 2023-09-09 | [('bentoml/onediffusion', 0.6226494908332825, 'diffusion', 0), ('openai/improved-diffusion', 0.5762985944747925, 'diffusion', 0), ('divamgupta/stable-diffusion-tensorflow', 0.5530334115028381, 'diffusion', 0), ('carson-katri/dream-textures', 0.5427067279815674, 'diffusion', 0)] | 6 | 5 | null | 3.52 | 110 | 20 | 12 | 4 | 0 | 0 | 0 | 109 | 175 | 90 | 1.6 | 70 |
1,102 | llm | https://github.com/tloen/alpaca-lora | ['llama', 'language-model'] | null | [] | [] | null | null | null | tloen/alpaca-lora | alpaca-lora | 17,713 | 2,161 | 156 | Jupyter Notebook | null | Instruct-tune LLaMA on consumer hardware | tloen | 2024-01-14 | 2023-03-13 | 46 | 383.873065 | null | Instruct-tune LLaMA on consumer hardware | [] | ['language-model', 'llama'] | 2023-04-18 | [('zrrskywalker/llama-adapter', 0.7604994773864746, 'llm', 2), ('microsoft/llama-2-onnx', 0.7532107830047607, 'llm', 2), ('facebookresearch/llama-recipes', 0.6903901100158691, 'llm', 2), ('jzhang38/tinyllama', 0.6666224598884583, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.663759171962738, 'llm', 0), ('run-llama/llama-lab', 0.6453814506530762, 'llm', 2), ('lightning-ai/lit-llama', 0.6250495314598083, 'llm', 2), ('facebookresearch/llama', 0.6226324439048767, 'llm', 2), ('ggerganov/llama.cpp', 0.6068325042724609, 'llm', 2), ('karpathy/llama2.c', 0.5766897201538086, 'llm', 2), ('abetlen/llama-cpp-python', 0.572754442691803, 'llm', 2), ('facebookresearch/codellama', 0.5405111908912659, 'llm', 2), ('run-llama/llama-hub', 0.5322900414466858, 'data', 0), ('hiyouga/llama-efficient-tuning', 0.5321193337440491, 'llm', 2), ('hiyouga/llama-factory', 0.5321192145347595, 'llm', 2), ('jerryjliu/llama_index', 0.5254223942756653, 'llm', 2), ('bentoml/openllm', 0.5242617726325989, 'ml-ops', 1), ('instruction-tuning-with-gpt-4/gpt-4-llm', 0.5178021788597107, 'llm', 1), ('ray-project/llm-applications', 0.5138564109802246, 'llm', 0), ('predibase/lorax', 0.507797122001648, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5027761459350586, 'perf', 0), ('tairov/llama2.mojo', 0.5015569925308228, 'llm', 1)] | 41 | 9 | null | 2.85 | 57 | 12 | 10 | 9 | 0 | 0 | 0 | 57 | 76 | 90 | 1.3 | 70 |
120 | ml-ops | https://github.com/mlflow/mlflow | [] | null | [] | [] | null | null | null | mlflow/mlflow | mlflow | 16,234 | 3,772 | 292 | Python | https://mlflow.org | Open source platform for the machine learning lifecycle | mlflow | 2024-01-13 | 2018-06-05 | 295 | 55.030508 | https://avatars.githubusercontent.com/u/39938107?v=4 | Open source platform for the machine learning lifecycle | ['ai', 'apache-spark', 'machine-learning', 'ml', 'mlflow', 'model-management'] | ['ai', 'apache-spark', 'machine-learning', 'ml', 'mlflow', 'model-management'] | 2024-01-12 | [('tensorflow/tensorflow', 0.7961823344230652, 'ml-dl', 2), ('polyaxon/polyaxon', 0.7237421870231628, 'ml-ops', 2), ('microsoft/nni', 0.6970524191856384, 'ml', 1), ('determined-ai/determined', 0.6798075437545776, 'ml-ops', 1), ('onnx/onnx', 0.6629000902175903, 'ml', 2), ('huggingface/datasets', 0.6532941460609436, 'nlp', 1), ('googlecloudplatform/vertex-ai-samples', 0.6433287262916565, 'ml', 2), ('netflix/metaflow', 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18 | 23 | 18 | 1,026 | 2,019 | 90 | 2 | 70 |
1,269 | data | https://github.com/qdrant/qdrant | ['vector-search'] | null | [] | [] | null | null | null | qdrant/qdrant | qdrant | 15,465 | 909 | 107 | Rust | https://qdrant.tech | Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ | qdrant | 2024-01-14 | 2020-05-30 | 191 | 80.787313 | https://avatars.githubusercontent.com/u/73504361?v=4 | Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/ | ['approximate-nearest-neighbor-search', 'embeddings-similarity', 'hnsw', 'image-search', 'knn-algorithm', 'machine-learning', 'matching', 'mlops', 'nearest-neighbor-search', 'neural-network', 'neural-search', 'recommender-system', 'search', 'search-engine', 'search-engines', 'similarity-search', 'vector-database', 'vector-search', 'vector-search-engine'] | ['approximate-nearest-neighbor-search', 'embeddings-similarity', 'hnsw', 'image-search', 'knn-algorithm', 'machine-learning', 'matching', 'mlops', 'nearest-neighbor-search', 'neural-network', 'neural-search', 'recommender-system', 'search', 'search-engine', 'search-engines', 'similarity-search', 'vector-database', 'vector-search', 'vector-search-engine'] | 2023-12-19 | [('marqo-ai/marqo', 0.7367421984672546, 'ml', 4), ('activeloopai/deeplake', 0.6835601329803467, 'ml-ops', 4), ('lancedb/lancedb', 0.6593559384346008, 'data', 7), ('jina-ai/vectordb', 0.5856242775917053, 'data', 3), ('qdrant/vector-db-benchmark', 0.582831621170044, 'perf', 3), ('googlecloudplatform/vertex-ai-samples', 0.5779662132263184, 'ml', 1), ('milvus-io/bootcamp', 0.5713267922401428, 'data', 2), ('qdrant/qdrant-haystack', 0.5697789788246155, 'data', 0), ('neuml/txtai', 0.5641199350357056, 'nlp', 7), ('mindsdb/mindsdb', 0.5584307312965393, 'data', 1), ('superduperdb/superduperdb', 0.5490362644195557, 'data', 2), ('hpcaitech/colossalai', 0.547572910785675, 'llm', 0), ('jina-ai/jina', 0.546108603477478, 'ml', 3), ('qdrant/quaterion', 0.5457815527915955, 'ml', 3), ('chroma-core/chroma', 0.5403642058372498, 'data', 0), ('docarray/docarray', 0.5395107865333557, 'data', 3), ('criteo/autofaiss', 0.5368368625640869, 'ml', 1), ('cheshire-cat-ai/core', 0.5352751016616821, 'llm', 1), ('bentoml/bentoml', 0.5326546430587769, 'ml-ops', 2), ('microsoft/nni', 0.526932418346405, 'ml', 3), ('tensorflow/similarity', 0.522907555103302, 'ml-dl', 3), ('tensorflow/tensorflow', 0.5152298808097839, 'ml-dl', 2), ('feast-dev/feast', 0.5136101245880127, 'ml-ops', 2), ('alirezadir/machine-learning-interview-enlightener', 0.5117506384849548, 'study', 1), ('mlflow/mlflow', 0.5098550915718079, 'ml-ops', 1), ('ray-project/ray', 0.5096204280853271, 'ml-ops', 1), ('qdrant/qdrant-client', 0.5091877579689026, 'util', 3)] | 78 | 4 | null | 20.4 | 682 | 550 | 44 | 1 | 24 | 17 | 24 | 682 | 880 | 90 | 1.3 | 70 |
121 | ml-ops | https://github.com/prefecthq/prefect | [] | null | [] | [] | null | null | null | prefecthq/prefect | prefect | 13,774 | 1,409 | 159 | Python | https://prefect.io | Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines | prefecthq | 2024-01-13 | 2018-06-29 | 291 | 47.240568 | https://avatars.githubusercontent.com/u/39270919?v=4 | Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines | ['automation', 'data', 'data-engineering', 'data-ops', 'data-science', 'infrastructure', 'ml-ops', 'observability', 'orchestration', 'pipeline', 'prefect', 'workflow', 'workflow-engine'] | ['automation', 'data', 'data-engineering', 'data-ops', 'data-science', 'infrastructure', 'ml-ops', 'observability', 'orchestration', 'pipeline', 'prefect', 'workflow', 'workflow-engine'] | 2024-01-13 | [('prefecthq/server', 0.7347409129142761, 'util', 5), ('kestra-io/kestra', 0.6422749757766724, 'ml-ops', 6), ('flyteorg/flyte', 0.6408464312553406, 'ml-ops', 3), ('dagster-io/dagster', 0.5984505414962769, 'ml-ops', 4), ('prefecthq/prefect-dbt', 0.5904790759086609, 'ml-ops', 1), ('mage-ai/mage-ai', 0.5904417037963867, 'ml-ops', 5), ('getindata/kedro-kubeflow', 0.5550775527954102, 'ml-ops', 0), ('apache/airflow', 0.5517212748527527, 'ml-ops', 6), ('astronomer/astro-sdk', 0.5360534191131592, 'ml-ops', 1), ('allegroai/clearml', 0.5174835324287415, 'ml-ops', 0), ('spotify/luigi', 0.5162726640701294, 'ml-ops', 0), ('ploomber/ploomber', 0.5095990896224976, 'ml-ops', 3), ('orchest/orchest', 0.5009967684745789, 'ml-ops', 1)] | 218 | 3 | null | 45.83 | 810 | 636 | 67 | 0 | 67 | 43 | 67 | 809 | 1,285 | 90 | 1.6 | 70 |
1,896 | nlp | https://github.com/myshell-ai/openvoice | [] | null | [] | [] | null | null | null | myshell-ai/openvoice | OpenVoice | 12,210 | 983 | 111 | Python | https://research.myshell.ai/open-voice | Instant voice cloning by MyShell. | myshell-ai | 2024-01-14 | 2023-11-29 | 8 | 1,378.548387 | https://avatars.githubusercontent.com/u/127754094?v=4 | Instant voice cloning by MyShell. | ['text-to-speech', 'tts', 'voice-clone', 'zero-shot-tts'] | ['text-to-speech', 'tts', 'voice-clone', 'zero-shot-tts'] | 2024-01-09 | [('plachtaa/vall-e-x', 0.6065437197685242, 'llm', 3), ('neonbjb/tortoise-tts', 0.57065349817276, 'ml', 1), ('vaibhavs10/insanely-fast-whisper', 0.5049346089363098, 'llm', 1)] | 8 | 4 | null | 1.25 | 103 | 45 | 2 | 0 | 0 | 0 | 0 | 103 | 244 | 90 | 2.4 | 70 |
532 | profiling | https://github.com/bloomberg/memray | [] | null | [] | [] | 1 | null | null | bloomberg/memray | memray | 11,750 | 383 | 58 | Python | https://bloomberg.github.io/memray/ | Memray is a memory profiler for Python | bloomberg | 2024-01-14 | 2022-04-08 | 94 | 124.244713 | https://avatars.githubusercontent.com/u/1416818?v=4 | Memray is a memory profiler for Python | ['memory', 'memory-leak', 'memory-leak-detection', 'memory-profiler', 'profiler'] | ['memory', 'memory-leak', 'memory-leak-detection', 'memory-profiler', 'profiler'] | 2024-01-12 | [('pythonspeed/filprofiler', 0.7156088352203369, 'profiling', 4), ('pympler/pympler', 0.5725077390670776, 'perf', 0), ('pythonprofilers/memory_profiler', 0.5463239550590515, 'profiling', 0)] | 42 | 5 | null | 4.33 | 45 | 38 | 22 | 0 | 8 | 11 | 8 | 45 | 94 | 90 | 2.1 | 70 |
1,802 | ml | https://github.com/microsoft/onnxruntime | [] | null | [] | [] | null | null | null | microsoft/onnxruntime | onnxruntime | 11,513 | 2,468 | 229 | C++ | https://onnxruntime.ai | ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator | microsoft | 2024-01-14 | 2018-11-10 | 272 | 42.260619 | https://avatars.githubusercontent.com/u/6154722?v=4 | ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator | ['ai-framework', 'deep-learning', 'hardware-acceleration', 'machine-learning', 'neural-networks', 'onnx', 'pytorch', 'scikit-learn', 'tensorflow'] | ['ai-framework', 'deep-learning', 'hardware-acceleration', 'machine-learning', 'neural-networks', 'onnx', 'pytorch', 'scikit-learn', 'tensorflow'] | 2024-01-14 | [('onnx/onnx', 0.727009654045105, 'ml', 6), ('tensorflow/tensorflow', 0.681681215763092, 'ml-dl', 3), ('tlkh/tf-metal-experiments', 0.6584108471870422, 'perf', 2), ('horovod/horovod', 0.6534867882728577, 'ml-ops', 4), ('determined-ai/determined', 0.643320620059967, 'ml-ops', 4), ('alpa-projects/alpa', 0.6340340971946716, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.6330754160881042, 'perf', 3), ('huggingface/datasets', 0.6271397471427917, 'nlp', 4), ('keras-team/keras', 0.6258196234703064, 'ml-dl', 5), ('neuralmagic/deepsparse', 0.6196989417076111, 'nlp', 1), ('pytorch/glow', 0.6179055571556091, 'ml', 0), ('pytorchlightning/pytorch-lightning', 0.5993390083312988, 'ml-dl', 3), ('explosion/thinc', 0.5988422632217407, 'ml-dl', 4), ('polyaxon/polyaxon', 0.5915482044219971, 'ml-ops', 4), ('tensorlayer/tensorlayer', 0.5911857485771179, 'ml-rl', 2), ('aiqc/aiqc', 0.5876568555831909, 'ml-ops', 0), ('nyandwi/modernconvnets', 0.5876009464263916, 'ml-dl', 2), ('google/tf-quant-finance', 0.5870956182479858, 'finance', 1), ('huggingface/transformers', 0.5852525234222412, 'nlp', 4), ('ray-project/ray', 0.5840818285942078, 'ml-ops', 4), ('mlflow/mlflow', 0.5830215811729431, 'ml-ops', 1), ('megvii-basedetection/yolox', 0.5817757844924927, 'ml', 3), ('nvidia/deeplearningexamples', 0.5810919404029846, 'ml-dl', 3), ('google/mediapipe', 0.5802665948867798, 'ml', 2), ('bentoml/bentoml', 0.5801241993904114, 'ml-ops', 2), ('intel/scikit-learn-intelex', 0.5744372010231018, 'perf', 2), ('jina-ai/jina', 0.57099848985672, 'ml', 2), ('aimhubio/aim', 0.5700400471687317, 'ml-ops', 3), ('skorch-dev/skorch', 0.5680661797523499, 'ml-dl', 3), ('pytorch/ignite', 0.5676509141921997, 'ml-dl', 3), ('apache/incubator-mxnet', 0.5671101212501526, 'ml-dl', 0), ('lutzroeder/netron', 0.5668833255767822, 'ml', 5), ('mosaicml/composer', 0.5664753317832947, 'ml-dl', 4), ('tensorflow/tensor2tensor', 0.564765214920044, 'ml', 2), ('microsoft/deepspeed', 0.5646995902061462, 'ml-dl', 3), ('google/trax', 0.5622458457946777, 'ml-dl', 2), ('bigscience-workshop/petals', 0.5610960721969604, 'data', 4), ('rasbt/machine-learning-book', 0.5571870803833008, 'study', 5), ('keras-rl/keras-rl', 0.5557011961936951, 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('deepmind/dm-haiku', 0.540787935256958, 'ml-dl', 3), ('mlc-ai/mlc-llm', 0.5396208763122559, 'llm', 0), ('activeloopai/deeplake', 0.5389828681945801, 'ml-ops', 4), ('project-monai/monai', 0.5315036773681641, 'ml', 2), ('opentensor/bittensor', 0.5280240774154663, 'ml', 4), ('koaning/human-learn', 0.5241006016731262, 'data', 2), ('rwightman/pytorch-image-models', 0.522943913936615, 'ml-dl', 1), ('lucidrains/imagen-pytorch', 0.519209623336792, 'ml-dl', 1), ('salesforce/warp-drive', 0.5185619592666626, 'ml-rl', 2), ('deci-ai/super-gradients', 0.5170263051986694, 'ml-dl', 2), ('roboflow/supervision', 0.5162255167961121, 'ml', 4), ('deepfakes/faceswap', 0.5149832963943481, 'ml-dl', 3), ('deepmind/dm_control', 0.5139978528022766, 'ml-rl', 3), ('aws/sagemaker-python-sdk', 0.513953447341919, 'ml', 3), ('xl0/lovely-tensors', 0.5118368864059448, 'ml-dl', 2), ('arogozhnikov/einops', 0.5109891295433044, 'ml-dl', 3), ('paddlepaddle/paddle', 0.5105121731758118, 'ml-dl', 2), ('cheshire-cat-ai/core', 0.5098522901535034, 'llm', 0), ('titanml/takeoff', 0.5081208348274231, 'llm', 0), ('keras-team/autokeras', 0.507604718208313, 'ml-dl', 3), ('alirezadir/machine-learning-interview-enlightener', 0.5041807293891907, 'study', 2), ('microsoft/jarvis', 0.5037975907325745, 'llm', 2), ('denys88/rl_games', 0.5028592348098755, 'ml-rl', 2), ('huggingface/huggingface_hub', 0.5021616816520691, 'ml', 3), ('neuralmagic/sparseml', 0.5017151236534119, 'ml-dl', 3)] | 579 | 1 | null | 53.08 | 1,524 | 1,068 | 63 | 0 | 8 | 9 | 8 | 1,521 | 4,180 | 90 | 2.7 | 70 |
1,014 | pandas | https://github.com/kanaries/pygwalker | [] | null | [] | [] | 1 | null | null | kanaries/pygwalker | pygwalker | 8,574 | 403 | 52 | Python | https://kanaries.net/home/pygwalker | PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis | kanaries | 2024-01-14 | 2023-02-16 | 49 | 172.465517 | https://avatars.githubusercontent.com/u/57262471?v=4 | PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis | ['data-analysis', 'data-exploration', 'dataframe', 'matplotlib', 'pandas', 'plotly', 'tableau', 'tableau-alternative', 'visualization'] | ['data-analysis', 'data-exploration', 'dataframe', 'matplotlib', 'pandas', 'plotly', 'tableau', 'tableau-alternative', 'visualization'] | 2024-01-11 | [('lux-org/lux', 0.7356677055358887, 'viz', 2), ('man-group/dtale', 0.7181293368339539, 'viz', 3), ('holoviz/panel', 0.6920881271362305, 'viz', 2), ('adamerose/pandasgui', 0.6812300682067871, 'pandas', 2), ('mwaskom/seaborn', 0.6736312508583069, 'viz', 2), ('plotly/plotly.py', 0.6529722809791565, 'viz', 2), ('bokeh/bokeh', 0.6463139653205872, 'viz', 1), ('tkrabel/bamboolib', 0.6401150822639465, 'pandas', 1), ('holoviz/holoviz', 0.6368023753166199, 'viz', 0), ('cuemacro/chartpy', 0.6271337270736694, 'viz', 2), ('holoviz/hvplot', 0.6253153085708618, 'pandas', 0), ('residentmario/geoplot', 0.6120375394821167, 'gis', 1), ('vizzuhq/ipyvizzu', 0.5989693403244019, 'jupyter', 0), ('altair-viz/altair', 0.5906645655632019, 'viz', 1), ('matplotlib/matplotlib', 0.5794761776924133, 'viz', 1), ('plotly/dash', 0.5757370591163635, 'viz', 1), ('federicoceratto/dashing', 0.569820761680603, 'term', 0), ('pyqtgraph/pyqtgraph', 0.5670520663261414, 'viz', 1), ('pandas-dev/pandas', 0.5644711256027222, 'pandas', 3), ('wesm/pydata-book', 0.5609186887741089, 'study', 0), ('jakevdp/pythondatasciencehandbook', 0.5599751472473145, 'study', 2), ('enthought/mayavi', 0.5563317537307739, 'viz', 1), ('holoviz/geoviews', 0.5505314469337463, 'gis', 0), ('scitools/iris', 0.5480643510818481, 'gis', 1), ('contextlab/hypertools', 0.5455514192581177, 'ml', 1), ('graphistry/pygraphistry', 0.5422446727752686, 'data', 2), ('quantopian/qgrid', 0.5393330454826355, 'jupyter', 0), ('datapane/datapane', 0.5378132462501526, 'viz', 0), ('opengeos/leafmap', 0.5377007722854614, 'gis', 1), ('maartenbreddels/ipyvolume', 0.5359721779823303, 'jupyter', 0), ('giswqs/geemap', 0.5327471494674683, 'gis', 0), ('alexmojaki/heartrate', 0.5303294658660889, 'debug', 1), ('rapidsai/cudf', 0.5281388759613037, 'pandas', 3), ('twopirllc/pandas-ta', 0.5264495611190796, 'finance', 2), ('vaexio/vaex', 0.5217480063438416, 'perf', 2), ('scitools/cartopy', 0.5204256772994995, 'gis', 1), ('matplotlib/mplfinance', 0.517193078994751, 'finance', 1), ('has2k1/plotnine', 0.5138752460479736, 'viz', 1), ('pyglet/pyglet', 0.5040571689605713, 'gamedev', 0), ('geopandas/geopandas', 0.5026245713233948, 'gis', 1), ('albahnsen/pycircular', 0.5010564923286438, 'math', 0)] | 13 | 5 | null | 7.79 | 131 | 114 | 11 | 0 | 46 | 53 | 46 | 131 | 85 | 90 | 0.6 | 70 |
1,515 | llm | https://github.com/facebookresearch/llama-recipes | ['llama', 'language-model'] | null | [] | [] | null | null | null | facebookresearch/llama-recipes | llama-recipes | 6,547 | 906 | 55 | Jupyter Notebook | null | Examples and recipes for Llama 2 model | facebookresearch | 2024-01-14 | 2023-07-17 | 28 | 232.634518 | https://avatars.githubusercontent.com/u/16943930?v=4 | Examples and recipes for Llama 2 model | [] | ['language-model', 'llama'] | 2024-01-12 | [('microsoft/llama-2-onnx', 0.820441722869873, 'llm', 2), ('facebookresearch/llama', 0.7843647003173828, 'llm', 2), ('karpathy/llama2.c', 0.7288556098937988, 'llm', 2), ('run-llama/llama-lab', 0.7252361178398132, 'llm', 2), ('tloen/alpaca-lora', 0.6903901100158691, 'llm', 2), ('jzhang38/tinyllama', 0.6900231242179871, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.6829999685287476, 'llm', 0), ('abetlen/llama-cpp-python', 0.6769752502441406, 'llm', 2), ('facebookresearch/codellama', 0.6740383505821228, 'llm', 2), ('ggerganov/llama.cpp', 0.6467329263687134, 'llm', 2), ('zrrskywalker/llama-adapter', 0.6457222700119019, 'llm', 2), ('tairov/llama2.mojo', 0.6153814792633057, 'llm', 1), ('lightning-ai/lit-llama', 0.5484828352928162, 'llm', 2), ('young-geng/easylm', 0.5477281212806702, 'llm', 2), ('cg123/mergekit', 0.5452256202697754, 'llm', 1), ('oobabooga/text-generation-webui', 0.5421599745750427, 'llm', 1), ('openlm-research/open_llama', 0.536719799041748, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5004853010177612, 'llm', 2), ('hiyouga/llama-factory', 0.5004853010177612, 'llm', 2)] | 46 | 4 | null | 8.65 | 139 | 73 | 6 | 0 | 0 | 0 | 0 | 139 | 189 | 90 | 1.4 | 70 |
587 | util | https://github.com/mingrammer/diagrams | [] | null | [] | [] | null | null | null | mingrammer/diagrams | diagrams | 32,318 | 2,122 | 377 | Python | https://diagrams.mingrammer.com | :art: Diagram as Code for prototyping cloud system architectures | mingrammer | 2024-01-14 | 2020-02-02 | 208 | 155.161866 | null | :art: Diagram as Code for prototyping cloud system architectures | ['architecture', 'diagram', 'diagram-as-code', 'graphviz'] | ['architecture', 'diagram', 'diagram-as-code', 'graphviz'] | 2024-01-05 | [('zenml-io/mlstacks', 0.5006417036056519, 'ml-ops', 0)] | 137 | 7 | null | 0.42 | 56 | 28 | 48 | 0 | 1 | 10 | 1 | 56 | 46 | 90 | 0.8 | 69 |
1,201 | ml | https://github.com/suno-ai/bark | ['multilingual', 'audio'] | null | [] | [] | null | null | null | suno-ai/bark | bark | 29,862 | 3,523 | 289 | Jupyter Notebook | null | π Text-Prompted Generative Audio Model | suno-ai | 2024-01-14 | 2023-04-07 | 42 | 701.456376 | https://avatars.githubusercontent.com/u/99442120?v=4 | π Text-Prompted Generative Audio Model | [] | ['audio', 'multilingual'] | 2023-09-28 | [('pollinations/dance-diffusion', 0.6367303729057312, 'diffusion', 1), ('facebookresearch/seamless_communication', 0.553849995136261, 'nlp', 0), ('thudm/chatglm-6b', 0.552562415599823, 'llm', 0), ('openai/finetune-transformer-lm', 0.5396863222122192, 'llm', 0), ('hazyresearch/ama_prompting', 0.5254032015800476, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5169947743415833, 'nlp', 0), ('keirp/automatic_prompt_engineer', 0.5167652368545532, 'llm', 0)] | 17 | 5 | null | 1.42 | 67 | 14 | 9 | 4 | 0 | 0 | 0 | 67 | 91 | 90 | 1.4 | 69 |
672 | ml-dl | https://github.com/facebookresearch/detectron2 | [] | null | [] | [] | null | null | null | facebookresearch/detectron2 | detectron2 | 27,792 | 7,230 | 380 | Python | https://detectron2.readthedocs.io/en/latest/ | Detectron2 is a platform for object detection, segmentation and other visual recognition tasks. | facebookresearch | 2024-01-14 | 2019-09-05 | 229 | 120.985075 | https://avatars.githubusercontent.com/u/16943930?v=4 | Detectron2 is a platform for object detection, segmentation and other visual recognition tasks. | [] | [] | 2024-01-09 | [('open-mmlab/mmdetection', 0.5715402960777283, 'ml', 0), ('roboflow/supervision', 0.5367303490638733, 'ml', 0), ('deci-ai/super-gradients', 0.5197049379348755, 'ml-dl', 0), ('nvlabs/gcvit', 0.504278838634491, 'diffusion', 0)] | 263 | 3 | null | 1.44 | 134 | 65 | 53 | 0 | 0 | 3 | 3 | 133 | 157 | 90 | 1.2 | 69 |
348 | ml | https://github.com/jina-ai/jina | [] | null | [] | [] | null | null | null | jina-ai/jina | jina | 19,552 | 2,201 | 205 | Python | https://docs.jina.ai | βοΈ Build multimodal AI applications with cloud-native stack | jina-ai | 2024-01-14 | 2020-02-13 | 206 | 94.584658 | https://avatars.githubusercontent.com/u/60539444?v=4 | βοΈ Build multimodal AI applications with cloud-native stack | ['cloud-native', 'cncf', 'deep-learning', 'docker', 'fastapi', 'framework', 'generative-ai', 'grpc', 'jaeger', 'kubernetes', 'llmops', 'machine-learning', 'microservice', 'mlops', 'multimodal', 'neural-search', 'opentelemetry', 'orchestration', 'pipeline', 'prometheus'] | ['cloud-native', 'cncf', 'deep-learning', 'docker', 'fastapi', 'framework', 'generative-ai', 'grpc', 'jaeger', 'kubernetes', 'llmops', 'machine-learning', 'microservice', 'mlops', 'multimodal', 'neural-search', 'opentelemetry', 'orchestration', 'pipeline', 'prometheus'] | 2024-01-10 | [('bentoml/bentoml', 0.692993700504303, 'ml-ops', 6), ('cheshire-cat-ai/core', 0.6241676807403564, 'llm', 1), ('googlecloudplatform/vertex-ai-samples', 0.6033614873886108, 'ml', 1), ('skypilot-org/skypilot', 0.5877841711044312, 'llm', 2), ('mlc-ai/mlc-llm', 0.581267774105072, 'llm', 0), ('microsoft/onnxruntime', 0.57099848985672, 'ml', 2), ('pathwaycom/llm-app', 0.567528486251831, 'llm', 2), ('hpcaitech/colossalai', 0.5669887065887451, 'llm', 1), ('netflix/metaflow', 0.5668376088142395, 'ml-ops', 3), ('lithops-cloud/lithops', 0.5622606873512268, 'ml-ops', 1), ('prefecthq/marvin', 0.5576962828636169, 'nlp', 0), ('polyaxon/polyaxon', 0.5560136437416077, 'ml-ops', 4), ('orchest/orchest', 0.5534289479255676, 'ml-ops', 3), ('uber/fiber', 0.5508025884628296, 'data', 1), ('horovod/horovod', 0.5503325462341309, 'ml-ops', 2), ('ray-project/ray', 0.5483666062355042, 'ml-ops', 2), ('google/mediapipe', 0.5477234125137329, 'ml', 3), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5461900234222412, 'web', 1), ('qdrant/qdrant', 0.546108603477478, 'data', 3), ('pytorchlightning/pytorch-lightning', 0.5442116260528564, 'ml-dl', 2), ('marqo-ai/marqo', 0.5435925126075745, 'ml', 2), ('alpa-projects/alpa', 0.5415318012237549, 'ml-dl', 2), ('zenml-io/zenml', 0.5385584831237793, 'ml-ops', 4), ('ml-tooling/opyrator', 0.5350887775421143, 'viz', 2), ('tensorflow/tensorflow', 0.5316888093948364, 'ml-dl', 2), ('activeloopai/deeplake', 0.5312637686729431, 'ml-ops', 3), ('docarray/docarray', 0.5284995436668396, 'data', 5), ('merantix-momentum/squirrel-core', 0.5257314443588257, 'ml', 2), ('stability-ai/stability-sdk', 0.524762749671936, 'diffusion', 1), ('luodian/otter', 0.5234236121177673, 'llm', 2), ('bodywork-ml/bodywork-core', 0.523324728012085, 'ml-ops', 6), ('antonosika/gpt-engineer', 0.5212904214859009, 'llm', 0), ('ludwig-ai/ludwig', 0.5165185332298279, 'ml-ops', 2), ('mlflow/mlflow', 0.5164972543716431, 'ml-ops', 1), ('determined-ai/determined', 0.5140607953071594, 'ml-ops', 4), ('zenml-io/mlstacks', 0.514028012752533, 'ml-ops', 1), ('tensorlayer/tensorlayer', 0.5102136135101318, 'ml-rl', 1), ('microsoft/semantic-kernel', 0.5081870555877686, 'llm', 0), ('adap/flower', 0.5048282146453857, 'ml-ops', 4), ('transformeroptimus/superagi', 0.5039621591567993, 'llm', 1), ('gradio-app/gradio', 0.5035788416862488, 'viz', 2), ('superduperdb/superduperdb', 0.5026459097862244, 'data', 2), ('eventual-inc/daft', 0.5019222497940063, 'pandas', 2), ('deepmind/dm_control', 0.5015859603881836, 'ml-rl', 2), ('lastmile-ai/aiconfig', 0.5008789300918579, 'util', 1)] | 176 | 2 | null | 6.81 | 198 | 181 | 48 | 0 | 25 | 99 | 25 | 198 | 172 | 90 | 0.9 | 69 |
280 | util | https://github.com/squidfunk/mkdocs-material | [] | null | [] | [] | null | null | null | squidfunk/mkdocs-material | mkdocs-material | 16,958 | 3,239 | 123 | HTML | https://squidfunk.github.io/mkdocs-material/ | Documentation that simply works | squidfunk | 2024-01-14 | 2016-01-28 | 417 | 40.597127 | null | Documentation that simply works | ['documentation', 'framework', 'material-design', 'mkdocs', 'plugins', 'theme'] | ['documentation', 'framework', 'material-design', 'mkdocs', 'plugins', 'theme'] | 2024-01-10 | [('mkdocstrings/mkdocstrings', 0.6913550496101379, 'util', 1), ('sphinx-doc/sphinx', 0.6544510126113892, 'util', 1), ('mitmproxy/pdoc', 0.6519834399223328, 'util', 1), ('mkdocs/mkdocs', 0.6341920495033264, 'util', 2), ('executablebooks/jupyter-book', 0.5147403478622437, 'jupyter', 0)] | 249 | 3 | null | 17.6 | 316 | 282 | 97 | 0 | 68 | 46 | 68 | 316 | 870 | 90 | 2.8 | 69 |
1,611 | llm | https://github.com/thudm/chatglm2-6b | [] | null | [] | [] | null | null | null | thudm/chatglm2-6b | ChatGLM2-6B | 14,854 | 2,347 | 130 | Python | null | ChatGLM2-6B: An Open Bilingual Chat LLM | εΌζΊεθ―ε―Ήθ―θ―θ¨ζ¨‘ε | thudm | 2024-01-14 | 2023-06-24 | 31 | 472.627273 | https://avatars.githubusercontent.com/u/48590610?v=4 | ChatGLM2-6B: An Open Bilingual Chat LLM | εΌζΊεθ―ε―Ήθ―θ―θ¨ζ¨‘ε | ['chatglm', 'chatglm-6b', 'large-language-models', 'llm'] | ['chatglm', 'chatglm-6b', 'large-language-models', 'llm'] | 2023-10-27 | [('li-plus/chatglm.cpp', 0.7250033617019653, 'llm', 2), ('thudm/chatglm-6b', 0.7089318633079529, 'llm', 0), ('nomic-ai/gpt4all', 0.6924757957458496, 'llm', 0), ('hwchase17/langchain', 0.6808525919914246, 'llm', 0), ('fasteval/fasteval', 0.6485232710838318, 'llm', 1), ('microsoft/autogen', 0.6360533237457275, 'llm', 0), ('mlc-ai/web-llm', 0.6331812143325806, 'llm', 1), ('next-gpt/next-gpt', 0.6282567381858826, 'llm', 2), ('lm-sys/fastchat', 0.6237083673477173, 'llm', 0), ('salesforce/xgen', 0.6184314489364624, 'llm', 2), ('young-geng/easylm', 0.601020097732544, 'llm', 1), ('intel/intel-extension-for-transformers', 0.6007229685783386, 'perf', 0), ('freedomintelligence/llmzoo', 0.5987119078636169, 'llm', 0), ('nat/openplayground', 0.5894226431846619, 'llm', 0), ('lchen001/llmdrift', 0.5880559086799622, 'llm', 0), ('cg123/mergekit', 0.58427494764328, 'llm', 1), ('dylanhogg/llmgraph', 0.580618679523468, 'ml', 1), ('openlmlab/moss', 0.5803049802780151, 'llm', 1), ('deep-diver/llm-as-chatbot', 0.5782683491706848, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.5761158466339111, 'llm', 3), ('hiyouga/llama-factory', 0.5761158466339111, 'llm', 3), ('baichuan-inc/baichuan-13b', 0.5701199173927307, 'llm', 1), ('bobazooba/xllm', 0.5669134855270386, 'llm', 2), ('lingjzhu/charsiug2p', 0.5563612580299377, 'nlp', 0), ('zhudotexe/kani', 0.5553779602050781, 'llm', 1), ('gunthercox/chatterbot-corpus', 0.5543924570083618, 'nlp', 0), ('eugeneyan/open-llms', 0.5501125454902649, 'study', 2), ('run-llama/rags', 0.547817587852478, 'llm', 1), ('hannibal046/awesome-llm', 0.5458086133003235, 'study', 0), ('infinitylogesh/mutate', 0.5451502203941345, 'nlp', 0), ('guidance-ai/guidance', 0.5406391024589539, 'llm', 0), ('explosion/spacy-llm', 0.5399860739707947, 'llm', 2), ('lianjiatech/belle', 0.5378761887550354, 'llm', 0), ('embedchain/embedchain', 0.5360315442085266, 'llm', 1), ('eleutherai/the-pile', 0.5338200330734253, 'data', 1), ('deepset-ai/haystack', 0.5324009656906128, 'llm', 1), ('confident-ai/deepeval', 0.5323322415351868, 'testing', 1), ('ctlllll/llm-toolmaker', 0.5311850309371948, 'llm', 0), ('ai21labs/lm-evaluation', 0.5304546356201172, 'llm', 0), ('sjtu-ipads/powerinfer', 0.5270649194717407, 'llm', 2), ('thudm/glm-130b', 0.5260385274887085, 'llm', 0), ('salesforce/codet5', 0.524960994720459, 'nlp', 1), ('langchain-ai/langgraph', 0.5230793356895447, 'llm', 0), ('aiwaves-cn/agents', 0.5184250473976135, 'nlp', 1), ('ray-project/ray-llm', 0.5179040431976318, 'llm', 2), ('whu-zqh/chatgpt-vs.-bert', 0.5137940645217896, 'llm', 0), ('night-chen/toolqa', 0.5134639143943787, 'llm', 1), ('chainlit/chainlit', 0.5131312608718872, 'llm', 1), ('cstankonrad/long_llama', 0.5114611387252808, 'llm', 0), ('pathwaycom/llm-app', 0.5088384747505188, 'llm', 1), ('zilliztech/gptcache', 0.507978081703186, 'llm', 1), ('microsoft/lora', 0.5071834921836853, 'llm', 0), ('databrickslabs/dolly', 0.506598949432373, 'llm', 0), ('juncongmoo/pyllama', 0.5058130621910095, 'llm', 0), ('bigscience-workshop/petals', 0.5052765607833862, 'data', 1), ('langchain-ai/chat-langchain', 0.5037407875061035, 'llm', 0), ('artidoro/qlora', 0.5035903453826904, 'llm', 0), ('blinkdl/chatrwkv', 0.5033798813819885, 'llm', 0), ('ibm/dromedary', 0.50322425365448, 'llm', 0), ('chatarena/chatarena', 0.5024993419647217, 'llm', 1), ('lupantech/chameleon-llm', 0.5024386644363403, 'llm', 1)] | 11 | 9 | null | 1.1 | 123 | 18 | 7 | 3 | 0 | 0 | 0 | 123 | 118 | 90 | 1 | 69 |
1,307 | study | https://github.com/hannibal046/awesome-llm | ['awesome', 'language-model', 'gpt'] | null | [] | [] | null | null | null | hannibal046/awesome-llm | Awesome-LLM | 11,253 | 847 | 293 | null | null | Awesome-LLM: a curated list of Large Language Model | hannibal046 | 2024-01-14 | 2023-02-17 | 49 | 227.005764 | null | Awesome-LLM: a curated list of Large Language Model | [] | ['awesome', 'gpt', 'language-model'] | 2024-01-04 | [('lianjiatech/belle', 0.8117328882217407, 'llm', 0), ('freedomintelligence/llmzoo', 0.7315229177474976, 'llm', 1), ('ai21labs/lm-evaluation', 0.725335955619812, 'llm', 1), ('ctlllll/llm-toolmaker', 0.708982527256012, 'llm', 1), ('juncongmoo/pyllama', 0.6920731067657471, 'llm', 0), ('next-gpt/next-gpt', 0.6860809922218323, 'llm', 0), ('guidance-ai/guidance', 0.6724131107330322, 'llm', 1), ('microsoft/autogen', 0.662517249584198, 'llm', 1), ('togethercomputer/redpajama-data', 0.6528944969177246, 'llm', 0), ('cg123/mergekit', 0.6510716080665588, 'llm', 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'llm', 1), ('1rgs/jsonformer', 0.5063848495483398, 'llm', 0), ('gkamradt/langchain-tutorials', 0.5057912468910217, 'study', 0), ('llmware-ai/llmware', 0.5052445530891418, 'llm', 0), ('cstankonrad/long_llama', 0.5006245970726013, 'llm', 1)] | 64 | 6 | null | 5.29 | 17 | 14 | 11 | 0 | 0 | 0 | 0 | 17 | 21 | 90 | 1.2 | 69 |
122 | ml-ops | https://github.com/dagster-io/dagster | [] | null | [] | [] | null | null | null | dagster-io/dagster | dagster | 9,380 | 1,160 | 108 | Python | https://dagster.io | An orchestration platform for the development, production, and observation of data assets. | dagster-io | 2024-01-14 | 2018-04-30 | 300 | 31.251785 | https://avatars.githubusercontent.com/u/40032576?v=4 | An orchestration platform for the development, production, and observation of data assets. | ['analytics', 'dagster', 'data-engineering', 'data-integration', 'data-orchestrator', 'data-pipelines', 'data-science', 'etl', 'metadata', 'mlops', 'orchestration', 'scheduler', 'workflow', 'workflow-automation'] | ['analytics', 'dagster', 'data-engineering', 'data-integration', 'data-orchestrator', 'data-pipelines', 'data-science', 'etl', 'metadata', 'mlops', 'orchestration', 'scheduler', 'workflow', 'workflow-automation'] | 2024-01-13 | [('flyteorg/flyte', 0.7850085496902466, 'ml-ops', 3), ('kestra-io/kestra', 0.7322535514831543, 'ml-ops', 7), ('airbytehq/airbyte', 0.6772870421409607, 'data', 3), ('mage-ai/mage-ai', 0.6750965714454651, 'ml-ops', 6), ('apache/airflow', 0.6647198796272278, 'ml-ops', 10), ('orchest/orchest', 0.6582160592079163, 'ml-ops', 3), ('avaiga/taipy', 0.6245914101600647, 'data', 4), ('netflix/metaflow', 0.6058613657951355, 'ml-ops', 2), ('meltano/meltano', 0.60458904504776, 'ml-ops', 2), ('ploomber/ploomber', 0.6021184325218201, 'ml-ops', 4), ('prefecthq/prefect', 0.5984505414962769, 'ml-ops', 4), ('dagworks-inc/hamilton', 0.5917893052101135, 'ml-ops', 5), ('polyaxon/polyaxon', 0.5835554003715515, 'ml-ops', 3), ('pydoit/doit', 0.5810200572013855, 'util', 3), ('bodywork-ml/bodywork-core', 0.5800526142120361, 'ml-ops', 3), ('backtick-se/cowait', 0.5563982725143433, 'util', 2), ('simonw/datasette', 0.5505277514457703, 'data', 0), ('prefecthq/server', 0.5430384278297424, 'util', 2), ('spotify/luigi', 0.5423729419708252, 'ml-ops', 0), ('astronomer/astro-sdk', 0.5415989756584167, 'ml-ops', 2), ('polyaxon/datatile', 0.5342531800270081, 'pandas', 2), ('fugue-project/fugue', 0.5329538583755493, 'pandas', 0), ('chaostoolkit/chaostoolkit', 0.5302633047103882, 'util', 0), ('dbt-labs/dbt-core', 0.5295764803886414, 'ml-ops', 1), ('databrickslabs/dbx', 0.5274744033813477, 'data', 1), ('saulpw/visidata', 0.515415370464325, 'term', 0), ('merantix-momentum/squirrel-core', 0.5139255523681641, 'ml', 1), ('featureform/embeddinghub', 0.512913703918457, 'nlp', 2), ('lithops-cloud/lithops', 0.5072967410087585, 'ml-ops', 0), ('kedro-org/kedro', 0.5058962106704712, 'ml-ops', 1)] | 380 | 4 | null | 78.85 | 1,651 | 1,070 | 70 | 0 | 66 | 125 | 66 | 1,649 | 2,509 | 90 | 1.5 | 69 |
83 | data | https://github.com/sqlalchemy/sqlalchemy | [] | null | [] | [] | null | null | null | sqlalchemy/sqlalchemy | sqlalchemy | 8,261 | 1,314 | 90 | Python | https://www.sqlalchemy.org | The Database Toolkit for Python | sqlalchemy | 2024-01-14 | 2018-11-27 | 270 | 30.596296 | https://avatars.githubusercontent.com/u/6043126?v=4 | The Database Toolkit for Python | ['sql', 'sqlalchemy'] | ['sql', 'sqlalchemy'] | 2024-01-13 | [('sqlalchemy/alembic', 0.8273295164108276, 'data', 2), ('tiangolo/sqlmodel', 0.8052466511726379, 'data', 2), ('agronholm/sqlacodegen', 0.7499924302101135, 'data', 0), ('ibis-project/ibis', 0.741746723651886, 'data', 2), ('mause/duckdb_engine', 0.6847227215766907, 'data', 2), ('mcfunley/pugsql', 0.6739656329154968, 'data', 1), ('andialbrecht/sqlparse', 0.6582309007644653, 'data', 0), ('simonw/sqlite-utils', 0.6196154952049255, 'data', 0), ('aminalaee/sqladmin', 0.6173149347305298, 'data', 1), ('tobymao/sqlglot', 0.6049283742904663, 'data', 1), ('collerek/ormar', 0.6017918586730957, 'data', 1), ('kayak/pypika', 0.5847384333610535, 'data', 1), ('malloydata/malloy-py', 0.5755621790885925, 'data', 1), ('macbre/sql-metadata', 0.5708635449409485, 'data', 1), ('aio-libs/aiopg', 0.5661270618438721, 'data', 1), ('tconbeer/harlequin', 0.5578516721725464, 'term', 1), ('aio-libs/aiomysql', 0.5567764043807983, 'data', 1), ('accenture/cymple', 0.5566608309745789, 'data', 0), ('machow/siuba', 0.5513966679573059, 'pandas', 1), ('eleutherai/pyfra', 0.5482377409934998, 'ml', 0), ('strawberry-graphql/strawberry', 0.5367457866668701, 'web', 0), ('pytables/pytables', 0.531848132610321, 'data', 0), ('aeternalis-ingenium/fastapi-backend-template', 0.5284538269042969, 'web', 1), ('pytoolz/toolz', 0.5267731547355652, 'util', 0), ('geopandas/geopandas', 0.5259225964546204, 'gis', 0), ('goldmansachs/gs-quant', 0.5246463418006897, 'finance', 0), ('sfu-db/connector-x', 0.5162760019302368, 'data', 1), ('jazzband/tablib', 0.5141265392303467, 'data', 0), ('python-cachier/cachier', 0.5100117921829224, 'perf', 0), ('falconry/falcon', 0.509283185005188, 'web', 0), ('nasdaq/data-link-python', 0.5085864067077637, 'finance', 0)] | 677 | 5 | null | 17.87 | 234 | 158 | 62 | 0 | 32 | 59 | 32 | 234 | 797 | 90 | 3.4 | 69 |
1,894 | nlp | https://github.com/m-bain/whisperx | [] | null | [] | [] | null | null | null | m-bain/whisperx | whisperX | 7,397 | 703 | 106 | Python | null | WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization) | m-bain | 2024-01-14 | 2022-12-09 | 59 | 124.170264 | null | WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization) | ['asr', 'speech', 'speech-recognition', 'speech-to-text', 'whisper'] | ['asr', 'speech', 'speech-recognition', 'speech-to-text', 'whisper'] | 2024-01-03 | [('uberi/speech_recognition', 0.6138349771499634, 'ml', 2), ('cmusphinx/pocketsphinx', 0.58738112449646, 'ml', 1), ('espnet/espnet', 0.5822861194610596, 'nlp', 1), ('ggerganov/whisper.cpp', 0.582147479057312, 'util', 3), ('speechbrain/speechbrain', 0.5771469473838806, 'nlp', 3), ('vaibhavs10/insanely-fast-whisper', 0.5447807312011719, 'llm', 1), ('nvidia/nemo', 0.5402535796165466, 'nlp', 3), ('facebookresearch/seamless_communication', 0.5283752083778381, 'nlp', 1), ('sanchit-gandhi/whisper-jax', 0.5212621688842773, 'ml', 3), ('nateshmbhat/pyttsx3', 0.5181179046630859, 'util', 0), ('pndurette/gtts', 0.509675920009613, 'util', 1), ('openai/whisper', 0.5077972412109375, 'ml-dl', 2), ('neonbjb/tortoise-tts', 0.5033969283103943, 'ml', 0), ('rasahq/rasa', 0.5019509792327881, 'llm', 0)] | 67 | 4 | null | 3.71 | 187 | 61 | 13 | 0 | 7 | 7 | 7 | 186 | 273 | 90 | 1.5 | 69 |
1,365 | llm | https://github.com/chainlit/chainlit | [] | null | [] | [] | null | null | null | chainlit/chainlit | chainlit | 4,315 | 504 | 43 | TypeScript | https://docs.chainlit.io | Build Python LLM apps in minutes β‘οΈ | chainlit | 2024-01-14 | 2023-03-14 | 46 | 93.804348 | https://avatars.githubusercontent.com/u/128686189?v=4 | Build Python LLM apps in minutes β‘οΈ | ['chatgpt', 'langchain', 'llm', 'openai', 'openai-chatgpt', 'ui'] | ['chatgpt', 'langchain', 'llm', 'openai', 'openai-chatgpt', 'ui'] | 2024-01-12 | [('berriai/litellm', 0.6367120742797852, 'llm', 3), ('hwchase17/langchain', 0.6356831789016724, 'llm', 1), ('shishirpatil/gorilla', 0.6185116171836853, 'llm', 2), ('mmabrouk/chatgpt-wrapper', 0.6109486222267151, 'llm', 3), ('run-llama/rags', 0.61057049036026, 'llm', 3), ('microsoft/promptflow', 0.6072118878364563, 'llm', 2), ('intel/intel-extension-for-transformers', 0.5824191570281982, 'perf', 0), ('microsoft/semantic-kernel', 0.5796830654144287, 'llm', 2), ('pathwaycom/llm-app', 0.5761844515800476, 'llm', 1), ('minimaxir/simpleaichat', 0.5655502080917358, 'llm', 1), ('nomic-ai/gpt4all', 0.5640503168106079, 'llm', 0), ('alphasecio/langchain-examples', 0.5578954815864563, 'llm', 3), ('citadel-ai/langcheck', 0.5534338355064392, 'llm', 0), ('deep-diver/llm-as-chatbot', 0.548169732093811, 'llm', 0), ('opengenerativeai/genossgpt', 0.5370033979415894, 'llm', 2), ('h2oai/h2o-llmstudio', 0.5345412492752075, 'llm', 2), ('microsoft/promptcraft-robotics', 0.5212441086769104, 'sim', 2), ('microsoft/autogen', 0.5154480338096619, 'llm', 1), ('exaloop/codon', 0.5148961544036865, 'perf', 0), ('thudm/chatglm2-6b', 0.5131312608718872, 'llm', 1), ('embedchain/embedchain', 0.5102947354316711, 'llm', 2), ('openai/openai-cookbook', 0.5076209306716919, 'ml', 2)] | 28 | 5 | null | 11.1 | 218 | 153 | 10 | 0 | 59 | 72 | 59 | 218 | 429 | 90 | 2 | 69 |
1,402 | security | https://github.com/swisskyrepo/payloadsallthethings | [] | null | [] | [] | null | null | null | swisskyrepo/payloadsallthethings | PayloadsAllTheThings | 54,665 | 13,867 | 1,762 | Python | https://swisskyrepo.github.io/PayloadsAllTheThings/ | A list of useful payloads and bypass for Web Application Security and Pentest/CTF | swisskyrepo | 2024-01-14 | 2016-10-18 | 380 | 143.855263 | null | A list of useful payloads and bypass for Web Application Security and Pentest/CTF | ['bounty', 'bugbounty', 'bypass', 'cheatsheet', 'enumeration', 'hacking', 'methodology', 'payload', 'payloads', 'penetration-testing', 'pentest', 'privilege-escalation', 'redteam', 'security', 'vulnerability', 'web-application'] | ['bounty', 'bugbounty', 'bypass', 'cheatsheet', 'enumeration', 'hacking', 'methodology', 'payload', 'payloads', 'penetration-testing', 'pentest', 'privilege-escalation', 'redteam', 'security', 'vulnerability', 'web-application'] | 2024-01-12 | [('flipkart-incubator/astra', 0.5459146499633789, 'web', 2), ('rhinosecuritylabs/pacu', 0.5338615775108337, 'security', 2), ('sqlmapproject/sqlmap', 0.5263312458992004, 'security', 0)] | 288 | 5 | null | 2.88 | 21 | 21 | 88 | 0 | 0 | 1 | 1 | 21 | 6 | 90 | 0.3 | 68 |
1,165 | ml-dl | https://github.com/facebookresearch/segment-anything | ['instance-segmentation', 'object-detection'] | null | [] | [] | null | null | null | facebookresearch/segment-anything | segment-anything | 41,500 | 4,868 | 287 | Jupyter Notebook | null | The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model. | facebookresearch | 2024-01-14 | 2023-03-23 | 44 | 928.115016 | https://avatars.githubusercontent.com/u/16943930?v=4 | The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model. | [] | ['instance-segmentation', 'object-detection'] | 2023-05-02 | [('matterport/mask_rcnn', 0.5424768328666687, 'ml-dl', 2), ('roboflow/notebooks', 0.51060950756073, 'study', 1)] | 16 | 5 | null | 0.67 | 159 | 29 | 10 | 9 | 0 | 0 | 0 | 159 | 259 | 90 | 1.6 | 68 |
1,381 | ml | https://github.com/google-research/google-research | [] | This repository contains code released by Google Research | [] | [] | null | null | null | google-research/google-research | google-research | 31,889 | 7,754 | 749 | Jupyter Notebook | https://research.google | Google Research | google-research | 2024-01-14 | 2018-10-04 | 277 | 114.826646 | https://avatars.githubusercontent.com/u/43830688?v=4 | Google Research | ['ai', 'machine-learning', 'research'] | ['ai', 'machine-learning', 'research'] | 2024-01-09 | [('google-research/language', 0.6985517740249634, 'nlp', 2), ('googlecloudplatform/vertex-ai-samples', 0.6550525426864624, 'ml', 1), ('alirezadir/machine-learning-interview-enlightener', 0.6368386745452881, 'study', 2), ('google-research/byt5', 0.6097835898399353, 'nlp', 0), ('google-research/t5x', 0.6067818999290466, 'ml', 0), ('tensorflow/tensor2tensor', 0.5845038890838623, 'ml', 1), ('xplainable/xplainable', 0.5756439566612244, 'ml-interpretability', 1), ('openbb-finance/openbbterminal', 0.5702900886535645, 'finance', 1), ('mindsdb/mindsdb', 0.5539237856864929, 'data', 2), ('bentoml/bentoml', 0.5528449416160583, 'ml-ops', 2), ('assafelovic/gpt-researcher', 0.545631468296051, 'llm', 0), ('hpcaitech/colossalai', 0.542206883430481, 'llm', 1), ('oneil512/insight', 0.5356377363204956, 'ml', 1), ('oegedijk/explainerdashboard', 0.5351460576057434, 'ml-interpretability', 0), ('google/dopamine', 0.5344747304916382, 'ml-rl', 1), ('firmai/industry-machine-learning', 0.5328598618507385, 'study', 1), ('mlflow/mlflow', 0.5312324166297913, 'ml-ops', 2), ('patchy631/machine-learning', 0.5150724053382874, 'ml', 0), ('iterative/dvc', 0.5124830603599548, 'ml-ops', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5109012126922607, 'study', 1), ('drivendata/cookiecutter-data-science', 0.5077729225158691, 'template', 2), ('pytorchlightning/pytorch-lightning', 0.5055912733078003, 'ml-dl', 2), ('seldonio/alibi', 0.5054081678390503, 'ml-interpretability', 1), ('automl/auto-sklearn', 0.5043892860412598, 'ml', 0), ('feast-dev/feast', 0.5038433074951172, 'ml-ops', 1)] | 763 | 3 | null | 10.79 | 136 | 26 | 64 | 0 | 0 | 0 | 0 | 136 | 96 | 90 | 0.7 | 68 |
1,183 | ml | https://github.com/facebookresearch/faiss | ['similarity', 'embeddings', 'vector-search'] | null | [] | [] | 1 | null | null | facebookresearch/faiss | faiss | 26,250 | 3,274 | 470 | C++ | https://faiss.ai | A library for efficient similarity search and clustering of dense vectors. | facebookresearch | 2024-01-14 | 2017-02-07 | 364 | 72.115385 | https://avatars.githubusercontent.com/u/16943930?v=4 | A library for efficient similarity search and clustering of dense vectors. | [] | ['embeddings', 'similarity', 'vector-search'] | 2024-01-13 | [('criteo/autofaiss', 0.629601776599884, 'ml', 3), ('qdrant/quaterion', 0.5449787378311157, 'ml', 0), ('qdrant/fastembed', 0.5384175777435303, 'ml', 2), ('plasticityai/magnitude', 0.5381598472595215, 'nlp', 1), ('qdrant/vector-db-benchmark', 0.5264250636100769, 'perf', 1), ('qdrant/qdrant-haystack', 0.518367350101471, 'data', 0), ('spotify/annoy', 0.5121656060218811, 'ml', 0), ('pinecone-io/pinecone-python-client', 0.5026112794876099, 'data', 1), ('nmslib/hnswlib', 0.5014215111732483, 'ml', 0)] | 150 | 6 | null | 4.33 | 163 | 82 | 84 | 0 | 1 | 3 | 1 | 163 | 287 | 90 | 1.8 | 68 |
45 | testing | https://github.com/locustio/locust | [] | null | [] | [] | 1 | null | null | locustio/locust | locust | 22,905 | 2,864 | 434 | Python | null | Write scalable load tests in plain Python ππ¨ | locustio | 2024-01-13 | 2011-02-17 | 675 | 33.897463 | https://avatars.githubusercontent.com/u/2641063?v=4 | Write scalable load tests in plain Python ππ¨ | ['benchmarking', 'http', 'load-generator', 'load-test', 'load-testing', 'load-tests', 'locust', 'performance', 'performance-testing'] | ['benchmarking', 'http', 'load-generator', 'load-test', 'load-testing', 'load-tests', 'locust', 'performance', 'performance-testing'] | 2024-01-11 | [('ionelmc/pytest-benchmark', 0.6405083537101746, 'testing', 2), ('klen/py-frameworks-bench', 0.6128438115119934, 'perf', 0), ('wolever/parameterized', 0.5832534432411194, 'testing', 0), ('neoteroi/blacksheep', 0.5740907192230225, 'web', 1), ('pmorissette/bt', 0.5575364828109741, 'finance', 0), ('sumerc/yappi', 0.5397162437438965, 'profiling', 1), ('encode/httpx', 0.5382368564605713, 'web', 1), ('joblib/joblib', 0.534275233745575, 'util', 0), ('requests/toolbelt', 0.5336475968360901, 'util', 1), ('falconry/falcon', 0.5264105200767517, 'web', 1), ('pympler/pympler', 0.5212385058403015, 'perf', 0), ('nedbat/coveragepy', 0.5198348760604858, 'testing', 0), ('pytest-dev/pytest', 0.5194878578186035, 'testing', 0), ('klen/muffin', 0.5192926526069641, 'web', 0), ('fastai/fastcore', 0.5126659870147705, 'util', 0), ('pallets/quart', 0.5093166828155518, 'web', 0), ('python-cachier/cachier', 0.5075251460075378, 'perf', 0), ('getsentry/responses', 0.5024783611297607, 'testing', 0)] | 312 | 6 | null | 6.92 | 163 | 154 | 157 | 0 | 14 | 9 | 14 | 163 | 376 | 90 | 2.3 | 68 |
1,168 | llm | https://github.com/microsoft/jarvis | [] | null | [] | [] | null | null | null | microsoft/jarvis | JARVIS | 22,433 | 1,941 | 376 | Python | null | JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf | microsoft | 2024-01-14 | 2023-03-30 | 43 | 513.173203 | https://avatars.githubusercontent.com/u/6154722?v=4 | JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf | ['deep-learning', 'platform', 'pytorch'] | ['deep-learning', 'platform', 'pytorch'] | 2024-01-12 | [('iryna-kondr/scikit-llm', 0.6588683128356934, 'llm', 1), ('vllm-project/vllm', 0.632617175579071, 'llm', 1), ('microsoft/torchscale', 0.5797202587127686, 'llm', 0), ('ludwig-ai/ludwig', 0.5734522342681885, 'ml-ops', 2), ('microsoft/semantic-kernel', 0.572293758392334, 'llm', 0), ('nomic-ai/gpt4all', 0.5687279105186462, 'llm', 0), ('bigscience-workshop/petals', 0.5665638446807861, 'data', 2), ('predibase/lorax', 0.5660221576690674, 'llm', 1), ('horovod/horovod', 0.5595570206642151, 'ml-ops', 2), ('bobazooba/xllm', 0.5591229200363159, 'llm', 2), ('nebuly-ai/nebullvm', 0.5589395761489868, 'perf', 0), ('tensorflow/tensor2tensor', 0.5555034279823303, 'ml', 1), ('alpha-vllm/llama2-accessory', 0.5535730719566345, 'llm', 0), ('tigerlab-ai/tiger', 0.552547812461853, 'llm', 0), ('aiqc/aiqc', 0.5510006546974182, 'ml-ops', 0), ('bentoml/openllm', 0.5471473336219788, 'ml-ops', 0), ('ray-project/ray-llm', 0.5456799268722534, 'llm', 0), ('tensorflow/tensorflow', 0.5449208617210388, 'ml-dl', 1), ('pathwaycom/llm-app', 0.544485330581665, 'llm', 0), ('rasbt/deeplearning-models', 0.5421392321586609, 'ml-dl', 0), ('truera/trulens', 0.5391638278961182, 'llm', 0), ('determined-ai/determined', 0.5367454290390015, 'ml-ops', 2), ('eugeneyan/open-llms', 0.5364652276039124, 'study', 0), ('mooler0410/llmspracticalguide', 0.5358785390853882, 'study', 0), ('paddlepaddle/paddle', 0.5339170098304749, 'ml-dl', 1), ('microsoft/lmops', 0.5317671895027161, 'llm', 0), ('young-geng/easylm', 0.5291217565536499, 'llm', 1), ('deepset-ai/haystack', 0.5287731885910034, 'llm', 1), ('argilla-io/argilla', 0.5283769369125366, 'nlp', 0), ('dylanhogg/llmgraph', 0.5276885032653809, 'ml', 0), ('uber/petastorm', 0.5265276432037354, 'data', 2), ('mrdbourke/pytorch-deep-learning', 0.5219099521636963, 'study', 2), ('deep-diver/llm-as-chatbot', 0.5197903513908386, 'llm', 0), ('mlflow/mlflow', 0.517335832118988, 'ml-ops', 0), ('intel/intel-extension-for-transformers', 0.5154780149459839, 'perf', 0), ('huggingface/datasets', 0.5145260691642761, 'nlp', 2), ('night-chen/toolqa', 0.5131213068962097, 'llm', 0), ('salesforce/xgen', 0.5117494463920593, 'llm', 0), ('titanml/takeoff', 0.5107346773147583, 'llm', 0), ('nvidia/tensorrt-llm', 0.5096875429153442, 'viz', 0), ('mlc-ai/mlc-llm', 0.5086725354194641, 'llm', 0), ('ddbourgin/numpy-ml', 0.5069154500961304, 'ml', 0), ('lamini-ai/llm-classifier', 0.5053083300590515, 'llm', 0), ('microsoft/onnxruntime', 0.5037975907325745, 'ml', 2), ('apache/incubator-mxnet', 0.5016826391220093, 'ml-dl', 0)] | 23 | 5 | null | 1.42 | 25 | 1 | 10 | 0 | 0 | 0 | 0 | 25 | 9 | 90 | 0.4 | 68 |
6 | viz | https://github.com/bokeh/bokeh | [] | null | [] | [] | null | null | null | bokeh/bokeh | bokeh | 18,477 | 4,202 | 443 | Python | https://bokeh.org | Interactive Data Visualization in the browser, from Python | bokeh | 2024-01-13 | 2012-03-26 | 618 | 29.891149 | https://avatars.githubusercontent.com/u/8440965?v=4 | Interactive Data Visualization in the browser, from Python | ['bokeh', 'data-visualisation', 'interactive-plots', 'javascript', 'jupyter', 'notebooks', 'numfocus', 'plots', 'plotting', 'visualisation', 'visualization'] | ['bokeh', 'data-visualisation', 'interactive-plots', 'javascript', 'jupyter', 'notebooks', 'numfocus', 'plots', 'plotting', 'visualisation', 'visualization'] | 2024-01-09 | [('holoviz/panel', 0.7603949308395386, 'viz', 2), ('plotly/plotly.py', 0.7521082758903503, 'viz', 1), ('plotly/dash', 0.7066522240638733, 'viz', 1), ('man-group/dtale', 0.6867046356201172, 'viz', 1), ('vizzuhq/ipyvizzu', 0.6746152639389038, 'jupyter', 2), ('maartenbreddels/ipyvolume', 0.6592708230018616, 'jupyter', 3), ('holoviz/holoviz', 0.6567468047142029, 'viz', 0), ('cuemacro/chartpy', 0.6531518697738647, 'viz', 2), ('kanaries/pygwalker', 0.6463139653205872, 'pandas', 1), ('matplotlib/matplotlib', 0.6447177529335022, 'viz', 1), ('giswqs/geemap', 0.6420087218284607, 'gis', 1), ('altair-viz/altair', 0.6335301399230957, 'viz', 1), ('residentmario/geoplot', 0.6318153738975525, 'gis', 0), ('mwaskom/seaborn', 0.6307612061500549, 'viz', 0), ('holoviz/hvplot', 0.6104094982147217, 'pandas', 1), ('opengeos/leafmap', 0.5971899032592773, 'gis', 1), ('nomic-ai/deepscatter', 0.594667911529541, 'viz', 1), ('python-visualization/folium', 0.5900196433067322, 'gis', 1), ('visgl/deck.gl', 0.5892252326011658, 'viz', 2), ('holoviz/geoviews', 0.5875713229179382, 'gis', 1), ('pyqtgraph/pyqtgraph', 0.5844684839248657, 'viz', 1), ('raphaelquast/eomaps', 0.5836126804351807, 'gis', 2), ('r0x0r/pywebview', 0.5825904607772827, 'gui', 1), ('has2k1/plotnine', 0.5768696069717407, 'viz', 1), ('alexmojaki/heartrate', 0.571494460105896, 'debug', 1), ('lux-org/lux', 0.5685267448425293, 'viz', 2), ('federicoceratto/dashing', 0.5679104924201965, 'term', 0), ('jiffyclub/snakeviz', 0.5664529204368591, 'profiling', 0), ('masoniteframework/masonite', 0.5602609515190125, 'web', 0), ('pyvista/pyvista', 0.559531569480896, 'viz', 2), ('seleniumbase/seleniumbase', 0.5535537004470825, 'testing', 0), ('westhealth/pyvis', 0.55198734998703, 'graph', 0), ('enthought/mayavi', 0.550900936126709, 'viz', 1), ('polyaxon/datatile', 0.5476343631744385, 'pandas', 0), ('gaogaotiantian/viztracer', 0.5466111302375793, 'profiling', 1), ('giswqs/mapwidget', 0.5409641861915588, 'gis', 1), ('contextlab/hypertools', 0.5384601950645447, 'ml', 1), ('mckinsey/vizro', 0.5383272171020508, 'viz', 1), ('hoffstadt/dearpygui', 0.5377543568611145, 'gui', 0), ('voila-dashboards/voila', 0.5361472368240356, 'jupyter', 1), ('webpy/webpy', 0.5360361933708191, 'web', 0), ('brandtbucher/specialist', 0.5352582931518555, 'perf', 0), ('pyglet/pyglet', 0.5342501401901245, 'gamedev', 0), ('klen/muffin', 0.5334693193435669, 'web', 0), ('willmcgugan/textual', 0.5320950150489807, 'term', 0), ('ranaroussi/quantstats', 0.5271790027618408, 'finance', 2), ('pyscript/pyscript', 0.5267843008041382, 'web', 1), ('jakevdp/pythondatasciencehandbook', 0.5242840051651001, 'study', 0), ('hazyresearch/meerkat', 0.5242655277252197, 'viz', 0), ('graphistry/pygraphistry', 0.5225502252578735, 'data', 2), ('pysimplegui/pysimplegui', 0.5222162008285522, 'gui', 0), ('vaexio/vaex', 0.5212001800537109, 'perf', 1), ('jalammar/ecco', 0.5211085081100464, 'ml-interpretability', 1), ('wesm/pydata-book', 0.5152010321617126, 'study', 0), ('matplotlib/mplfinance', 0.5142570734024048, 'finance', 0), ('imageio/imageio', 0.5136635303497314, 'util', 0), ('parthjadhav/tkinter-designer', 0.5127165913581848, 'gui', 0), ('jupyter-widgets/ipywidgets', 0.5115343928337097, 'jupyter', 0), ('vispy/vispy', 0.5114392638206482, 'viz', 1), ('eleutherai/pyfra', 0.5110460519790649, 'ml', 0), ('microsoft/playwright-python', 0.510855495929718, 'testing', 0), ('scitools/iris', 0.5092189908027649, 'gis', 1), ('pygraphviz/pygraphviz', 0.5085844993591309, 'viz', 0), ('gregorhd/mapcompare', 0.5074924826622009, 'gis', 1), ('urwid/urwid', 0.5072845816612244, 'term', 0), ('wxwidgets/phoenix', 0.5054352879524231, 'gui', 0), ('scitools/cartopy', 0.5045799612998962, 'gis', 0), ('roniemartinez/dude', 0.5035302042961121, 'util', 0), ('adamerose/pandasgui', 0.5031503438949585, 'pandas', 0), ('wandb/client', 0.5021753907203674, 'ml', 0)] | 680 | 5 | null | 8.69 | 330 | 228 | 144 | 0 | 0 | 9 | 9 | 330 | 712 | 90 | 2.2 | 68 |
1,172 | llm | https://github.com/yoheinakajima/babyagi | ['autonomous-agents', 'artificial-intelligence'] | GPT-4 powered task-driven autonomous agent | [] | [] | null | null | null | yoheinakajima/babyagi | babyagi | 18,298 | 2,473 | 280 | Python | null | null | yoheinakajima | 2024-01-14 | 2023-04-03 | 43 | 424.125828 | null | GPT-4 powered task-driven autonomous agent | [] | ['artificial-intelligence', 'autonomous-agents'] | 2023-09-07 | [('assafelovic/gpt-researcher', 0.6752115488052368, 'llm', 0), ('linksoul-ai/autoagents', 0.6577290892601013, 'llm', 1), ('torantulino/auto-gpt', 0.6121024489402771, 'llm', 2), ('antonosika/gpt-engineer', 0.5550106763839722, 'llm', 0), ('operand/agency', 0.53130042552948, 'llm', 2), ('transformeroptimus/superagi', 0.5311616659164429, 'llm', 2), ('geekan/metagpt', 0.5191521644592285, 'llm', 0)] | 87 | 5 | null | 5.17 | 6 | 2 | 10 | 4 | 0 | 1 | 1 | 6 | 1 | 90 | 0.2 | 68 |
75 | typing | https://github.com/python/mypy | ['code-quality'] | null | [] | [] | null | null | null | python/mypy | mypy | 17,020 | 2,765 | 236 | Python | https://www.mypy-lang.org/ | Optional static typing for Python | python | 2024-01-13 | 2012-12-07 | 581 | 29.265537 | https://avatars.githubusercontent.com/u/1525981?v=4 | Optional static typing for Python | ['linter', 'typechecker', 'types', 'typing'] | ['code-quality', 'linter', 'typechecker', 'types', 'typing'] | 2024-01-14 | [('microsoft/pyright', 0.8244960904121399, 'typing', 2), ('google/pytype', 0.7456424236297607, 'typing', 5), ('agronholm/typeguard', 0.7131239771842957, 'typing', 2), ('instagram/monkeytype', 0.7129145264625549, 'typing', 1), ('python/typeshed', 0.6911789178848267, 'typing', 3), ('facebook/pyre-check', 0.628227949142456, 'typing', 2), ('instagram/fixit', 0.5660220384597778, 'util', 1), ('patrick-kidger/torchtyping', 0.5514424443244934, 'typing', 1), ('tiangolo/typer', 0.5458303093910217, 'term', 0), ('grantjenks/blue', 0.5406695604324341, 'util', 1), ('landscapeio/prospector', 0.5345390439033508, 'util', 0), ('astral-sh/ruff', 0.533256471157074, 'util', 2), ('pytoolz/toolz', 0.5248755216598511, 'util', 0), ('psf/black', 0.5155326128005981, 'util', 1), ('pycqa/pylint', 0.5039985179901123, 'util', 2), ('pycqa/pyflakes', 0.5037577748298645, 'util', 1)] | 690 | 4 | null | 16.1 | 739 | 373 | 135 | 0 | 0 | 8 | 8 | 737 | 1,435 | 90 | 1.9 | 68 |
766 | ml-dl | https://github.com/sanster/lama-cleaner | [] | null | [] | [] | null | null | null | sanster/lama-cleaner | lama-cleaner | 14,764 | 1,530 | 119 | Python | https://lama-cleaner-docs.vercel.app/ | Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures. | sanster | 2024-01-14 | 2021-11-15 | 115 | 128.223325 | null | Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures. | ['inpainting', 'lama', 'latent-diffusion', 'mat', 'pytorch', 'stable-diffusion', 'zits'] | ['inpainting', 'lama', 'latent-diffusion', 'mat', 'pytorch', 'stable-diffusion', 'zits'] | 2024-01-08 | [('open-mmlab/mmediting', 0.5644564032554626, 'ml', 2), ('invoke-ai/invokeai', 0.551865816116333, 'diffusion', 3), ('lkwq007/stablediffusion-infinity', 0.5446968078613281, 'diffusion', 2), ('carson-katri/dream-textures', 0.5392587780952454, 'diffusion', 1), ('timothybrooks/instruct-pix2pix', 0.5218861699104309, 'diffusion', 0), ('automatic1111/stable-diffusion-webui', 0.5176366567611694, 'diffusion', 2), ('albumentations-team/albumentations', 0.515965461730957, 'ml-dl', 0), ('roboflow/notebooks', 0.5101523995399475, 'study', 1)] | 14 | 5 | null | 3.37 | 31 | 12 | 26 | 0 | 11 | 23 | 11 | 31 | 39 | 90 | 1.3 | 68 |
407 | web | https://github.com/aio-libs/aiohttp | [] | null | [] | [] | null | null | null | aio-libs/aiohttp | aiohttp | 14,277 | 1,996 | 222 | Python | https://docs.aiohttp.org | Asynchronous HTTP client/server framework for asyncio and Python | aio-libs | 2024-01-14 | 2013-10-01 | 539 | 26.487941 | https://avatars.githubusercontent.com/u/7049303?v=4 | Asynchronous HTTP client/server framework for asyncio and Python | ['aiohttp', 'async', 'asyncio', 'http', 'http-client', 'http-server'] | ['aiohttp', 'async', 'asyncio', 'http', 'http-client', 'http-server'] | 2024-01-12 | [('encode/httpx', 0.8457793593406677, 'web', 2), ('encode/uvicorn', 0.7939640879631042, 'web', 3), ('pallets/quart', 0.7800691723823547, 'web', 2), ('neoteroi/blacksheep', 0.7317296862602234, 'web', 3), ('alirn76/panther', 0.7044265270233154, 'web', 0), ('magicstack/uvloop', 0.6718955636024475, 'util', 2), ('miguelgrinberg/python-socketio', 0.6701440215110779, 'util', 1), ('agronholm/anyio', 0.6634643077850342, 'perf', 1), ('timofurrer/awesome-asyncio', 0.6443581581115723, 'study', 1), ('aio-libs/aiobotocore', 0.6436625719070435, 'util', 2), ('python-trio/trio', 0.6344983577728271, 'perf', 1), ('samuelcolvin/aioaws', 0.6308304667472839, 'data', 1), ('encode/starlette', 0.6300008296966553, 'web', 2), ('samuelcolvin/arq', 0.6253662705421448, 'data', 2), ('geeogi/async-python-lambda-template', 0.5915722250938416, 'template', 0), ('ets-labs/python-dependency-injector', 0.5857105255126953, 'util', 2), ('tiangolo/asyncer', 0.5814606547355652, 'perf', 2), ('alex-sherman/unsync', 0.5807369351387024, 'util', 0), ('klen/muffin', 0.5731057524681091, 'web', 1), ('pytest-dev/pytest-asyncio', 0.5665972828865051, 'testing', 1), ('aio-libs/aiokafka', 0.5572373270988464, 'data', 1), ('airtai/faststream', 0.5545108914375305, 'perf', 1), ('cherrypy/cherrypy', 0.5461557507514954, 'web', 2), ('huge-success/sanic', 0.5445988774299622, 'web', 1), ('sumerc/yappi', 0.5396091341972351, 'profiling', 1), ('tornadoweb/tornado', 0.5350281596183777, 'web', 0), ('psf/requests', 0.5318570137023926, 'web', 1), ('websocket-client/websocket-client', 0.5178495049476624, 'web', 0), ('pylons/waitress', 0.5173540711402893, 'web', 1), ('falconry/falcon', 0.512401819229126, 'web', 1), ('requests/toolbelt', 0.5097265839576721, 'util', 1), ('simple-salesforce/simple-salesforce', 0.5096431970596313, 'data', 0), ('jordaneremieff/mangum', 0.5083812475204468, 'web', 1), ('hugapi/hug', 0.5045132040977478, 'util', 2), ('replicate/replicate-python', 0.5043667554855347, 'ml', 0)] | 708 | 5 | null | 8.79 | 385 | 315 | 125 | 0 | 8 | 24 | 8 | 381 | 1,111 | 90 | 2.9 | 68 |
381 | llm | https://github.com/deepset-ai/haystack | ['haystack'] | null | [] | [] | 1 | null | null | deepset-ai/haystack | haystack | 12,318 | 1,539 | 121 | Python | https://haystack.deepset.ai | :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots. | deepset-ai | 2024-01-14 | 2019-11-14 | 219 | 56.063719 | https://avatars.githubusercontent.com/u/51827949?v=4 | :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots. | ['ai', 'bert', 'chatgpt', 'generative-ai', 'gpt-3', 'information-retrieval', 'language-model', 'large-language-models', 'machine-learning', 'nlp', 'pytorch', 'question-answering', 'semantic-search', 'squad', 'summarization', 'transformers'] | ['ai', 'bert', 'chatgpt', 'generative-ai', 'gpt-3', 'haystack', 'information-retrieval', 'language-model', 'large-language-models', 'machine-learning', 'nlp', 'pytorch', 'question-answering', 'semantic-search', 'squad', 'summarization', 'transformers'] | 2024-01-12 | [('pathwaycom/llm-app', 0.7468881607055664, 'llm', 1), ('llmware-ai/llmware', 0.6901717185974121, 'llm', 11), ('nomic-ai/gpt4all', 0.6876985430717468, 'llm', 1), ('embedchain/embedchain', 0.6720160841941833, 'llm', 2), ('rcgai/simplyretrieve', 0.67171311378479, 'llm', 4), ('paddlepaddle/paddlenlp', 0.6606729626655579, 'llm', 4), 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80 | math | https://github.com/scipy/scipy | [] | null | [] | [] | null | null | null | scipy/scipy | scipy | 12,076 | 4,979 | 349 | Python | https://scipy.org | SciPy library main repository | scipy | 2024-01-13 | 2011-03-09 | 672 | 17.947346 | https://avatars.githubusercontent.com/u/288277?v=4 | SciPy library main repository | ['algorithms', 'scientific-computing', 'scipy'] | ['algorithms', 'scientific-computing', 'scipy'] | 2024-01-14 | [('numpy/numpy', 0.7627651691436768, 'math', 0), ('scikit-geometry/scikit-geometry', 0.6300176382064819, 'gis', 0), ('sympy/sympy', 0.6143859028816223, 'math', 0), ('roban/cosmolopy', 0.6138890385627747, 'sim', 0), ('dask/dask', 0.6020888686180115, 'perf', 1), ('cma-es/pycma', 0.5867729187011719, 'math', 0), ('scikit-learn/scikit-learn', 0.5719190835952759, 'ml', 0), ('scikit-hep/uproot5', 0.5634987354278564, 'data', 0), ('gbeced/pyalgotrade', 0.5615862011909485, 'finance', 0), ('fredrik-johansson/mpmath', 0.5546449422836304, 'math', 0), ('pysal/pysal', 0.5544923543930054, 'gis', 0), ('cupy/cupy', 0.5399492979049683, 'math', 1), ('scikit-optimize/scikit-optimize', 0.5384607911109924, 'ml', 1), ('pycaret/pycaret', 0.5348325967788696, 'ml', 0), ('jakevdp/pythondatasciencehandbook', 0.5299432873725891, 'study', 0), ('thealgorithms/python', 0.5260889530181885, 'study', 0), ('scikit-learn-contrib/metric-learn', 0.5236490368843079, 'ml', 0), ('pyston/pyston', 0.5205775499343872, 'util', 0), ('eleutherai/pyfra', 0.5191806554794312, 'ml', 0), ('pypy/pypy', 0.5184841156005859, 'util', 0), ('pytoolz/toolz', 0.5162753462791443, 'util', 0), ('mynameisfiber/high_performance_python_2e', 0.5127685070037842, 'study', 0), ('marcomusy/vedo', 0.5084977746009827, 'viz', 0), ('joblib/joblib', 0.508256196975708, 'util', 0), ('probml/pyprobml', 0.5070646405220032, 'ml', 0), ('life4/textdistance', 0.5068709850311279, 'nlp', 1), ('crflynn/stochastic', 0.5048527121543884, 'sim', 0), ('krzjoa/awesome-python-data-science', 0.5031641721725464, 'study', 0), ('pmorissette/ffn', 0.502606987953186, 'finance', 0), ('networkx/networkx', 0.5018213391304016, 'graph', 0), ('python/cpython', 0.500981867313385, 'util', 0), ('quantopian/zipline', 0.5005958080291748, 'finance', 0), ('rasbt/mlxtend', 0.5000782012939453, 'ml', 0)] | 1,572 | 4 | null | 42.25 | 891 | 449 | 156 | 0 | 10 | 12 | 10 | 891 | 2,493 | 90 | 2.8 | 68 |
1,390 | finance | https://github.com/ai4finance-foundation/fingpt | ['language-model', 'llm'] | null | [] | [] | null | null | null | ai4finance-foundation/fingpt | FinGPT | 10,239 | 2,162 | 209 | Jupyter Notebook | https://discord.gg/trsr8SXpW5 | Data-Centric FinGPT. Open-source for open finance! Revolutionize π₯ We release the trained model on HuggingFace. | ai4finance-foundation | 2024-01-14 | 2023-02-11 | 50 | 203.03966 | https://avatars.githubusercontent.com/u/68813910?v=4 | Data-Centric FinGPT. Open-source for open finance! Revolutionize π₯ We release the trained model on HuggingFace. | ['chatgpt', 'finance', 'fingpt', 'fintech', 'large-language-models', 'machine-learning', 'nlp', 'prompt-engineering', 'pytorch', 'reinforcement-learning', 'robo-advisor', 'sentiment-analysis', 'technical-analysis'] | ['chatgpt', 'finance', 'fingpt', 'fintech', 'language-model', 'large-language-models', 'llm', 'machine-learning', 'nlp', 'prompt-engineering', 'pytorch', 'reinforcement-learning', 'robo-advisor', 'sentiment-analysis', 'technical-analysis'] | 2023-12-26 | [('chancefocus/pixiu', 0.7477177381515503, 'finance', 8), ('ai4finance-foundation/finrl', 0.6304659247398376, 'finance', 3), ('argilla-io/argilla', 0.5461266040802002, 'nlp', 3), ('doccano/doccano', 0.5407078862190247, 'nlp', 1), ('lianjiatech/belle', 0.5230826735496521, 'llm', 0), ('mindsdb/mindsdb', 0.5226989984512329, 'data', 2), ('ta-lib/ta-lib-python', 0.5139918327331543, 'finance', 2), ('xtekky/gpt4free', 0.5088690519332886, 'llm', 2), ('bobazooba/xllm', 0.5081082582473755, 'llm', 4), ('goldmansachs/gs-quant', 0.5048463344573975, 'finance', 0)] | 27 | 8 | null | 10.44 | 51 | 27 | 11 | 1 | 0 | 0 | 0 | 51 | 55 | 90 | 1.1 | 68 |
200 | ml | https://github.com/huggingface/accelerate | [] | null | [] | [] | null | null | null | huggingface/accelerate | accelerate | 6,340 | 710 | 95 | Python | https://huggingface.co/docs/accelerate | π A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision | huggingface | 2024-01-14 | 2020-10-30 | 169 | 37.388374 | https://avatars.githubusercontent.com/u/25720743?v=4 | π A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision | [] | [] | 2024-01-12 | [('nvidia/apex', 0.7648141980171204, 'ml-dl', 0), ('pytorch/ignite', 0.6613282561302185, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.6329745650291443, 'perf', 0), ('skorch-dev/skorch', 0.6029394268989563, 'ml-dl', 0), ('pytorch/pytorch', 0.5829792022705078, 'ml-dl', 0), ('laekov/fastmoe', 0.5827643275260925, 'ml', 0), ('blackhc/toma', 0.5751364827156067, 'ml-dl', 0), ('mrdbourke/pytorch-deep-learning', 0.5736592411994934, 'study', 0), ('hysts/pytorch_image_classification', 0.5682789087295532, 'ml-dl', 0), ('eleutherai/gpt-neo', 0.5675502419471741, 'llm', 0), ('arogozhnikov/einops', 0.5633874535560608, 'ml-dl', 0), ('tensorflow/mesh', 0.5616391897201538, 'ml-dl', 0), ('pytorchlightning/pytorch-lightning', 0.5604153871536255, 'ml-dl', 0), ('pytorch/data', 0.5591470003128052, 'data', 0), ('nicolas-chaulet/torch-points3d', 0.5572007894515991, 'ml', 0), ('xl0/lovely-tensors', 0.557181715965271, 'ml-dl', 0), ('karpathy/mingpt', 0.5470962524414062, 'llm', 0), ('denys88/rl_games', 0.5460307002067566, 'ml-rl', 0), ('rentruewang/koila', 0.5446726083755493, 'ml', 0), ('cupy/cupy', 0.5428050756454468, 'math', 0), ('ashleve/lightning-hydra-template', 0.5420671105384827, 'util', 0), ('pytorch/captum', 0.5386924743652344, 'ml-interpretability', 0), ('nvidia/tensorrt-llm', 0.5342060923576355, 'viz', 0), ('salesforce/warp-drive', 0.5263185501098633, 'ml-rl', 0), ('rasbt/machine-learning-book', 0.5255182385444641, 'study', 0), ('karpathy/micrograd', 0.5209835767745972, 'study', 0), ('cvxgrp/pymde', 0.5172093510627747, 'ml', 0), ('rasbt/deeplearning-models', 0.5161780714988708, 'ml-dl', 0), ('nvidia/warp', 0.5148420333862305, 'sim', 0), ('pyg-team/pytorch_geometric', 0.514308750629425, 'ml-dl', 0), ('google/tf-quant-finance', 0.5086351633071899, 'finance', 0), ('timdettmers/bitsandbytes', 0.5063002705574036, 'util', 0), ('pytorch/rl', 0.5024619102478027, 'ml-rl', 0)] | 209 | 5 | null | 11.67 | 394 | 338 | 39 | 0 | 17 | 13 | 17 | 394 | 1,100 | 90 | 2.8 | 68 |
1,751 | llm | https://github.com/dsdanielpark/bard-api | [] | null | [] | [] | null | null | null | dsdanielpark/bard-api | Bard-API | 5,245 | 661 | 46 | Python | https://pypi.org/project/bardapi/ | The unofficial python package that returns response of Google Bard through cookie value. | dsdanielpark | 2024-01-14 | 2023-05-11 | 37 | 139.07197 | null | The unofficial python package that returns response of Google Bard through cookie value. | ['ai-api', 'api', 'bard', 'bard-api', 'chatbot', 'google', 'google-bard', 'google-bard-api', 'google-bard-python', 'google-maps-api', 'googlebard', 'llm', 'nlp'] | ['ai-api', 'api', 'bard', 'bard-api', 'chatbot', 'google', 'google-bard', 'google-bard-api', 'google-bard-python', 'google-maps-api', 'googlebard', 'llm', 'nlp'] | 2024-01-14 | [('googleapis/google-api-python-client', 0.6036682724952698, 'util', 0), ('psf/requests', 0.5480201244354248, 'web', 0), ('googleapis/python-speech', 0.5438737273216248, 'ml', 0), ('pndurette/gtts', 0.5274245738983154, 'util', 0)] | 26 | 1 | null | 12.79 | 59 | 35 | 8 | 0 | 37 | 58 | 37 | 59 | 168 | 90 | 2.8 | 68 |
689 | ml-dl | https://github.com/deepfakes/faceswap | [] | null | [] | [] | null | null | null | deepfakes/faceswap | faceswap | 48,131 | 12,869 | 1,526 | Python | https://www.faceswap.dev | Deepfakes Software For All | deepfakes | 2024-01-14 | 2017-12-19 | 319 | 150.880878 | null | Deepfakes Software For All | ['deep-face-swap', 'deep-learning', 'deep-neural-networks', 'deepface', 'deepfakes', 'deeplearning', 'face-swap', 'faceswap', 'fakeapp', 'machine-learning', 'myfakeapp', 'neural-nets', 'neural-networks', 'openfaceswap'] | ['deep-face-swap', 'deep-learning', 'deep-neural-networks', 'deepface', 'deepfakes', 'deeplearning', 'face-swap', 'faceswap', 'fakeapp', 'machine-learning', 'myfakeapp', 'neural-nets', 'neural-networks', 'openfaceswap'] | 2024-01-12 | [('iperov/deepfacelab', 0.8627434968948364, 'ml-dl', 12), ('huggingface/exporters', 0.5523707270622253, 'ml', 2), ('huggingface/transformers', 0.5490606427192688, 'nlp', 2), ('huggingface/huggingface_hub', 0.5489972233772278, 'ml', 2), ('explosion/thinc', 0.5478455424308777, 'ml-dl', 2), ('christoschristofidis/awesome-deep-learning', 0.5433439612388611, 'study', 2), ('rwightman/pytorch-image-models', 0.5423110127449036, 'ml-dl', 0), ('tencentarc/gfpgan', 0.5402413606643677, 'ml', 1), ('neuralmagic/sparseml', 0.5372126698493958, 'ml-dl', 0), ('fepegar/torchio', 0.5368450880050659, 'ml-dl', 2), ('keras-team/keras', 0.5320166945457458, 'ml-dl', 3), ('alpa-projects/alpa', 0.5312798619270325, 'ml-dl', 2), ('neuralmagic/deepsparse', 0.5284426212310791, 'nlp', 0), ('huggingface/autotrain-advanced', 0.5193936228752136, 'ml', 2), ('huggingface/datasets', 0.5192609429359436, 'nlp', 2), ('microsoft/onnxruntime', 0.5149832963943481, 'ml', 3), ('roboflow/supervision', 0.5128257274627686, 'ml', 2), ('nvidia/deeplearningexamples', 0.5123569965362549, 'ml-dl', 1), ('mosaicml/composer', 0.5090040564537048, 'ml-dl', 3), ('awslabs/autogluon', 0.5015328526496887, 'ml', 2), ('onnx/onnx', 0.5000324845314026, 'ml', 3)] | 97 | 2 | null | 1.52 | 20 | 19 | 74 | 0 | 2 | 1 | 2 | 20 | 22 | 90 | 1.1 | 67 |
1,054 | llm | https://github.com/moymix/taskmatrix | ['chatgpt'] | Connects ChatGPT and a series of Visual Foundation Models to enable sending and receiving images during chatting. | [] | [] | null | null | null | moymix/taskmatrix | TaskMatrix | 34,397 | 3,381 | 310 | Python | null | null | moymix | 2024-01-14 | 2023-03-02 | 47 | 720.89521 | null | Connects ChatGPT and a series of Visual Foundation Models to enable sending and receiving images during chatting. | [] | ['chatgpt'] | 2023-06-29 | [('next-gpt/next-gpt', 0.5018583536148071, 'llm', 1)] | 20 | 5 | null | 1.73 | 21 | 6 | 11 | 7 | 0 | 0 | 0 | 21 | 23 | 90 | 1.1 | 67 |
76 | nlp | https://github.com/pytorch/fairseq | [] | null | [] | [] | null | null | null | pytorch/fairseq | fairseq | 28,464 | 6,285 | 417 | Python | null | Facebook AI Research Sequence-to-Sequence Toolkit written in Python. | pytorch | 2024-01-14 | 2017-08-29 | 335 | 84.967164 | https://avatars.githubusercontent.com/u/16943930?v=4 | Facebook AI Research Sequence-to-Sequence Toolkit written in Python. | ['artificial-intelligence', 'pytorch'] | ['artificial-intelligence', 'pytorch'] | 2024-01-08 | [('facebookresearch/mmf', 0.6375062465667725, 'ml-dl', 1), ('deepmind/deepmind-research', 0.5041647553443909, 'ml', 0)] | 421 | 4 | null | 0.77 | 134 | 40 | 78 | 0 | 0 | 3 | 3 | 134 | 116 | 90 | 0.9 | 67 |
8 | perf | https://github.com/celery/celery | [] | null | [] | [] | null | null | null | celery/celery | celery | 22,871 | 4,604 | 473 | Python | https://docs.celeryq.dev | Distributed Task Queue (development branch) | celery | 2024-01-13 | 2009-04-24 | 770 | 29.680571 | https://avatars.githubusercontent.com/u/319983?v=4 | Distributed Task Queue (development branch) | ['amqp', 'queue-tasks', 'queue-workers', 'queued-jobs', 'redis', 'redis-queue', 'sqs', 'sqs-queue', 'task-manager', 'task-runner', 'task-scheduler'] | ['amqp', 'queue-tasks', 'queue-workers', 'queued-jobs', 'redis', 'redis-queue', 'sqs', 'sqs-queue', 'task-manager', 'task-runner', 'task-scheduler'] | 2024-01-11 | [('mher/flower', 0.6660754680633545, 'perf', 1), ('samuelcolvin/arq', 0.5360067486763, 'data', 1)] | 1,327 | 6 | null | 6.65 | 278 | 167 | 179 | 0 | 8 | 16 | 8 | 280 | 513 | 90 | 1.8 | 67 |
1,121 | llm | https://github.com/rasahq/rasa | [] | null | [] | ['rasa'] | null | null | null | rasahq/rasa | rasa | 17,448 | 4,498 | 350 | Python | https://rasa.com/docs/rasa/ | π¬ Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants | rasahq | 2024-01-14 | 2016-10-14 | 380 | 45.846847 | https://avatars.githubusercontent.com/u/21214473?v=4 | π¬ Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants | ['bot', 'bot-framework', 'botkit', 'bots', 'chatbot', 'chatbots', 'chatbots-framework', 'conversation-driven-development', 'conversational-agents', 'conversational-ai', 'conversational-bots', 'machine-learning', 'machine-learning-library', 'mitie', 'natural-language-processing', 'nlp', 'nlu', 'rasa', 'spacy', 'wit'] | ['bot', 'bot-framework', 'botkit', 'bots', 'chatbot', 'chatbots', 'chatbots-framework', 'conversation-driven-development', 'conversational-agents', 'conversational-ai', 'conversational-bots', 'machine-learning', 'machine-learning-library', 'mitie', 'natural-language-processing', 'nlp', 'nlu', 'rasa', 'spacy', 'wit'] | 2023-11-29 | [('deeppavlov/deeppavlov', 0.7903884053230286, 'nlp', 4), ('nvidia/nemo', 0.7352750301361084, 'nlp', 1), ('krohling/bondai', 0.7222825288772583, 'llm', 0), ('embedchain/embedchain', 0.7189019322395325, 'llm', 1), ('gunthercox/chatterbot', 0.6935678720474243, 'nlp', 3), ('togethercomputer/openchatkit', 0.6932374835014343, 'nlp', 1), ('openlmlab/moss', 0.6797881126403809, 'llm', 1), ('lm-sys/fastchat', 0.6786299347877502, 'llm', 1), ('rcgai/simplyretrieve', 0.660693347454071, 'llm', 3), ('aiwaves-cn/agents', 0.6561240553855896, 'nlp', 0), ('nomic-ai/gpt4all', 0.6559364199638367, 'llm', 1), ('databrickslabs/dolly', 0.6492189168930054, 'llm', 1), ('nltk/nltk', 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0), ('uberi/speech_recognition', 0.5011873245239258, 'ml', 0)] | 592 | 5 | null | 29.4 | 138 | 109 | 88 | 2 | 70 | 93 | 70 | 138 | 103 | 90 | 0.7 | 67 |
1,780 | web | https://github.com/wagtail/wagtail | [] | null | [] | [] | null | null | null | wagtail/wagtail | wagtail | 16,554 | 3,542 | 341 | Python | https://wagtail.org | A Django content management system focused on flexibility and user experience | wagtail | 2024-01-14 | 2014-02-03 | 521 | 31.764803 | https://avatars.githubusercontent.com/u/23708009?v=4 | A Django content management system focused on flexibility and user experience | ['cms', 'django', 'wagtail'] | ['cms', 'django', 'wagtail'] | 2024-01-11 | [('feincms/feincms', 0.7559544444084167, 'web', 1), ('stephenmcd/mezzanine', 0.7118169665336609, 'web', 2), ('django/django', 0.5955774188041687, 'web', 1), ('brettkromkamp/contextualise', 0.5667254328727722, 'data', 0), ('pallets/flask', 0.5286979675292969, 'web', 0), ('fastapi-admin/fastapi-admin', 0.5146538019180298, 'web', 0), ('indico/indico', 0.5091932415962219, 'web', 0), ('piccolo-orm/piccolo_admin', 0.5042932033538818, 'data', 1)] | 880 | 3 | null | 40.79 | 622 | 368 | 121 | 4 | 30 | 24 | 30 | 623 | 1,539 | 90 | 2.5 | 67 |
1,510 | llm | https://github.com/facebookresearch/codellama | ['llama', 'language-model'] | null | [] | [] | null | null | null | facebookresearch/codellama | codellama | 11,969 | 1,192 | 125 | Python | null | Inference code for CodeLlama models | facebookresearch | 2024-01-14 | 2023-08-24 | 22 | 526.937107 | https://avatars.githubusercontent.com/u/16943930?v=4 | Inference code for CodeLlama models | [] | ['language-model', 'llama'] | 2023-09-26 | [('facebookresearch/llama', 0.8860641121864319, 'llm', 2), ('karpathy/llama2.c', 0.7492680549621582, 'llm', 2), ('facebookresearch/llama-recipes', 0.6740383505821228, 'llm', 2), ('microsoft/llama-2-onnx', 0.6238771080970764, 'llm', 2), ('tairov/llama2.mojo', 0.599827229976654, 'llm', 1), ('jzhang38/tinyllama', 0.5828747749328613, 'llm', 2), ('abetlen/llama-cpp-python', 0.5786312222480774, 'llm', 2), ('openai/gpt-2', 0.550112247467041, 'llm', 0), ('juncongmoo/pyllama', 0.5494055151939392, 'llm', 0), ('lightning-ai/lit-llama', 0.5444297790527344, 'llm', 2), ('tloen/alpaca-lora', 0.5405111908912659, 'llm', 2), ('openlm-research/open_llama', 0.5370882153511047, 'llm', 2), ('salesforce/codet5', 0.5207399725914001, 'nlp', 1), ('cg123/mergekit', 0.51674485206604, 'llm', 1), ('cstankonrad/long_llama', 0.5162266492843628, 'llm', 2), ('hazyresearch/h3', 0.513182520866394, 'llm', 0), ('mshumer/gpt-llm-trainer', 0.509406328201294, 'llm', 0), ('freedomintelligence/llmzoo', 0.508786141872406, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5052860975265503, 'llm', 1), ('bigcode-project/starcoder', 0.5031982064247131, 'llm', 0), ('hao-ai-lab/lookaheaddecoding', 0.5007719397544861, 'llm', 0)] | 11 | 6 | null | 0.27 | 58 | 19 | 5 | 4 | 0 | 0 | 0 | 58 | 69 | 90 | 1.2 | 67 |
72 | testing | https://github.com/pytest-dev/pytest | [] | null | [] | [] | null | null | null | pytest-dev/pytest | pytest | 10,981 | 2,471 | 192 | Python | https://pytest.org | The pytest framework makes it easy to write small tests, yet scales to support complex functional testing | pytest-dev | 2024-01-13 | 2015-06-15 | 450 | 24.394478 | https://avatars.githubusercontent.com/u/8897583?v=4 | The pytest framework makes it easy to write small tests, yet scales to support complex functional testing | ['test', 'testing', 'unit-testing'] | ['test', 'testing', 'unit-testing'] | 2024-01-14 | [('ionelmc/pytest-benchmark', 0.6786613464355469, 'testing', 0), ('samuelcolvin/dirty-equals', 0.6580618023872375, 'util', 1), ('pytest-dev/pytest-xdist', 0.6530086994171143, 'testing', 0), ('pytest-dev/pytest-mock', 0.6347528100013733, 'testing', 0), ('samuelcolvin/pytest-pretty', 0.5827073454856873, 'testing', 0), ('wolever/parameterized', 0.5712449550628662, 'testing', 0), ('pytest-dev/pytest-asyncio', 0.5557228922843933, 'testing', 1), ('pytest-dev/pytest-testinfra', 0.5438085794448853, 'testing', 1), ('teemu/pytest-sugar', 0.5432929992675781, 'testing', 1), ('pytest-dev/pytest-cov', 0.5345095992088318, 'testing', 0), ('taverntesting/tavern', 0.5295860767364502, 'testing', 1), ('locustio/locust', 0.5194878578186035, 'testing', 0), ('computationalmodelling/nbval', 0.5131306648254395, 'jupyter', 1), ('pmorissette/bt', 0.5103425979614258, 'finance', 0), ('hypothesisworks/hypothesis', 0.505795955657959, 'testing', 1)] | 934 | 5 | null | 13.98 | 384 | 265 | 104 | 0 | 10 | 23 | 10 | 384 | 745 | 90 | 1.9 | 67 |
1,654 | util | https://github.com/pyo3/pyo3 | ['rust'] | null | [] | [] | null | null | null | pyo3/pyo3 | pyo3 | 10,178 | 669 | 84 | Rust | https://pyo3.rs | Rust bindings for the Python interpreter | pyo3 | 2024-01-14 | 2017-05-13 | 350 | 29.044435 | https://avatars.githubusercontent.com/u/28156855?v=4 | Rust bindings for the Python interpreter | ['binding', 'ffi', 'python-c-api', 'rust'] | ['binding', 'ffi', 'python-c-api', 'rust'] | 2024-01-13 | [('pyo3/rust-numpy', 0.6885672211647034, 'util', 1), ('pyo3/maturin', 0.6540318131446838, 'util', 1), ('rustpython/rustpython', 0.6475306749343872, 'util', 1), ('delta-io/delta-rs', 0.5582752227783203, 'pandas', 1), ('pybind/pybind11', 0.5454217791557312, 'perf', 0), ('samuelcolvin/rtoml', 0.5289204716682434, 'data', 1)] | 301 | 5 | null | 10.88 | 229 | 174 | 81 | 0 | 10 | 12 | 10 | 228 | 662 | 90 | 2.9 | 67 |
534 | nlp | https://github.com/nvidia/nemo | [] | null | [] | [] | null | null | null | nvidia/nemo | NeMo | 8,946 | 1,977 | 180 | Python | https://nvidia.github.io/NeMo/ | NeMo: a toolkit for conversational AI | nvidia | 2024-01-14 | 2019-08-05 | 234 | 38.207444 | https://avatars.githubusercontent.com/u/1728152?v=4 | NeMo: a toolkit for conversational AI | ['asr', 'deep-learning', 'language-model', 'machine-translation', 'neural-network', 'nlp', 'nlp-machine-learning', 'nmt', 'speaker-diarization', 'speaker-recognition', 'speech-recognition', 'speech-synthesis', 'speech-to-text', 'text-normalization', 'text-to-speech', 'tts'] | ['asr', 'deep-learning', 'language-model', 'machine-translation', 'neural-network', 'nlp', 'nlp-machine-learning', 'nmt', 'speaker-diarization', 'speaker-recognition', 'speech-recognition', 'speech-synthesis', 'speech-to-text', 'text-normalization', 'text-to-speech', 'tts'] | 2024-01-13 | [('deeppavlov/deeppavlov', 0.7471092939376831, 'nlp', 3), ('rasahq/rasa', 0.7352750301361084, 'llm', 1), ('krohling/bondai', 0.7121801972389221, 'llm', 0), ('facebookresearch/parlai', 0.6826277375221252, 'nlp', 0), ('thilinarajapakse/simpletransformers', 0.6740487813949585, 'nlp', 0), ('openlmlab/moss', 0.640605628490448, 'llm', 2), ('espnet/espnet', 0.63554447889328, 'nlp', 5), ('speechbrain/speechbrain', 0.6236434578895569, 'nlp', 7), ('rcgai/simplyretrieve', 0.6101846098899841, 'llm', 1), ('gunthercox/chatterbot', 0.5878262519836426, 'nlp', 0), ('databrickslabs/dolly', 0.5758463144302368, 'llm', 0), ('cheshire-cat-ai/core', 0.5682287216186523, 'llm', 0), ('lm-sys/fastchat', 0.5640174150466919, 'llm', 1), ('embedchain/embedchain', 0.5636201500892639, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5635098218917847, 'nlp', 0), ('prefecthq/marvin', 0.560585081577301, 'nlp', 0), ('keras-team/keras-nlp', 0.5545443892478943, 'nlp', 2), ('huggingface/transformers', 0.5480668544769287, 'nlp', 4), ('fasteval/fasteval', 0.5468846559524536, 'llm', 0), ('minimaxir/aitextgen', 0.5452271699905396, 'llm', 0), ('minimaxir/simpleaichat', 0.5450947284698486, 'llm', 0), ('explosion/spacy', 0.541452169418335, 'nlp', 3), ('alirezadir/machine-learning-interview-enlightener', 0.5406086444854736, 'study', 1), ('m-bain/whisperx', 0.5402535796165466, 'nlp', 3), ('togethercomputer/openchatkit', 0.5391964912414551, 'nlp', 0), ('allenai/allennlp', 0.5374099016189575, 'nlp', 2), ('deepset-ai/haystack', 0.5352417826652527, 'llm', 2), ('alibaba/easynlp', 0.527443528175354, 'nlp', 2), ('chatarena/chatarena', 0.5267899036407471, 'llm', 0), ('nvidia/deeplearningexamples', 0.5229525566101074, 'ml-dl', 4), ('facebookresearch/mmf', 0.5225995779037476, 'ml-dl', 1), ('microsoft/generative-ai-for-beginners', 0.5218424201011658, 'study', 1), ('nltk/nltk', 0.5199841260910034, 'nlp', 1), ('blinkdl/chatrwkv', 0.5173482894897461, 'llm', 1), ('graykode/nlp-tutorial', 0.5165086388587952, 'study', 1), ('facebookresearch/seamless_communication', 0.5158795714378357, 'nlp', 2), ('gventuri/pandas-ai', 0.513568639755249, 'pandas', 0), ('microsoft/lmops', 0.5125614404678345, 'llm', 2), ('bentoml/bentoml', 0.5116295218467712, 'ml-ops', 1), ('lucidrains/toolformer-pytorch', 0.5109055042266846, 'llm', 2), ('ddbourgin/numpy-ml', 0.5102659463882446, 'ml', 0), ('nomic-ai/gpt4all', 0.5101531744003296, 'llm', 1), ('explosion/thinc', 0.5100991129875183, 'ml-dl', 2), ('franck-dernoncourt/neuroner', 0.5075932145118713, 'nlp', 2), ('llmware-ai/llmware', 0.503142237663269, 'llm', 1), ('minimaxir/textgenrnn', 0.5010759234428406, 'nlp', 1)] | 270 | 2 | null | 18.33 | 527 | 432 | 54 | 0 | 10 | 11 | 10 | 526 | 1,411 | 90 | 2.7 | 67 |
1,162 | web | https://github.com/flet-dev/flet | [] | null | [] | [] | null | null | null | flet-dev/flet | flet | 7,928 | 303 | 110 | Python | https://flet.dev | Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required. | flet-dev | 2024-01-14 | 2022-03-24 | 96 | 81.973412 | https://avatars.githubusercontent.com/u/102273996?v=4 | Flet enables developers to easily build realtime web, mobile and desktop apps in Python. No frontend experience required. | ['android', 'flutter', 'ios', 'server-driven-ui', 'web'] | ['android', 'flutter', 'ios', 'server-driven-ui', 'web'] | 2024-01-12 | [('pallets/flask', 0.6681143045425415, 'web', 0), ('willmcgugan/textual', 0.6341605186462402, 'term', 0), ('reflex-dev/reflex', 0.612991988658905, 'web', 0), ('kivy/kivy', 0.6066066026687622, 'util', 2), ('python-restx/flask-restx', 0.6032120585441589, 'web', 0), ('r0x0r/pywebview', 0.5987342000007629, 'gui', 0), ('klen/muffin', 0.5684182643890381, 'web', 0), ('pallets/quart', 0.5679628252983093, 'web', 0), ('webpy/webpy', 0.5566127896308899, 'web', 0), ('bottlepy/bottle', 0.5521423816680908, 'web', 0), ('plotly/dash', 0.5519179105758667, 'viz', 0), ('falconry/falcon', 0.5503961443901062, 'web', 1), ('huge-success/sanic', 0.5318177342414856, 'web', 1), ('masoniteframework/masonite', 0.5303350687026978, 'web', 1), ('starlite-api/starlite', 0.5249883532524109, 'web', 0), ('tiangolo/fastapi', 0.5213461518287659, 'web', 1), ('vitalik/django-ninja', 0.5206228494644165, 'web', 0), ('alphasecio/langchain-examples', 0.5201708078384399, 'llm', 0), ('pallets/werkzeug', 0.5143693089485168, 'web', 0), ('timofurrer/awesome-asyncio', 0.5139799118041992, 'study', 0), ('hoffstadt/dearpygui', 0.5117893815040588, 'gui', 0), ('neoteroi/blacksheep', 0.5072730183601379, 'web', 1), ('pyinfra-dev/pyinfra', 0.5072339773178101, 'util', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5064703822135925, 'template', 0), ('holoviz/panel', 0.5036301016807556, 'viz', 0)] | 47 | 3 | null | 4.54 | 399 | 254 | 22 | 0 | 34 | 60 | 34 | 400 | 677 | 90 | 1.7 | 67 |
1,290 | llm | https://github.com/optimalscale/lmflow | ['instruction-following', 'language-model'] | null | [] | [] | null | null | null | optimalscale/lmflow | LMFlow | 7,551 | 1,077 | 72 | Python | https://optimalscale.github.io/LMFlow/ | An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All. | optimalscale | 2024-01-13 | 2023-03-27 | 44 | 171.058252 | https://avatars.githubusercontent.com/u/128913633?v=4 | An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All. | ['chatgpt', 'deep-learning', 'instruction-following', 'language-model', 'pretrained-models', 'pytorch', 'transformer'] | ['chatgpt', 'deep-learning', 'instruction-following', 'language-model', 'pretrained-models', 'pytorch', 'transformer'] | 2023-12-02 | [('juncongmoo/pyllama', 0.6721161007881165, 'llm', 0), ('guardrails-ai/guardrails', 0.6163129210472107, 'llm', 0), ('tatsu-lab/stanford_alpaca', 0.6111303567886353, 'llm', 3), ('huggingface/text-generation-inference', 0.6065784692764282, 'llm', 3), ('hpcaitech/energonai', 0.6059041619300842, 'ml', 0), ('next-gpt/next-gpt', 0.5973320603370667, 'llm', 1), ('lianjiatech/belle', 0.5924107432365417, 'llm', 0), ('nvidia/deeplearningexamples', 0.5852581858634949, 'ml-dl', 2), ('huggingface/datasets', 0.578310489654541, 'nlp', 2), ('hannibal046/awesome-llm', 0.5771458745002747, 'study', 1), ('cg123/mergekit', 0.5650473237037659, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.5642813444137573, 'llm', 1), ('hiyouga/llama-factory', 0.5642813444137573, 'llm', 1), ('huggingface/transformers', 0.5635979771614075, 'nlp', 5), ('ctlllll/llm-toolmaker', 0.5597103238105774, 'llm', 1), ('openbmb/toolbench', 0.5591222643852234, 'llm', 0), ('rafiqhasan/auto-tensorflow', 0.5579131841659546, 'ml-dl', 0), ('microsoft/torchscale', 0.5554569959640503, 'llm', 1), ('young-geng/easylm', 0.5390665531158447, 'llm', 3), ('microsoft/unilm', 0.5366694331169128, 'nlp', 0), ('microsoft/autogen', 0.5350280404090881, 'llm', 1), ('databrickslabs/dolly', 0.5335168242454529, 'llm', 0), ('vllm-project/vllm', 0.5301596522331238, 'llm', 2), ('guidance-ai/guidance', 0.5283278226852417, 'llm', 2), ('bobazooba/xllm', 0.5273640751838684, 'llm', 3), ('ai21labs/lm-evaluation', 0.5266632437705994, 'llm', 1), ('lm-sys/fastchat', 0.5264976620674133, 'llm', 1), ('infinitylogesh/mutate', 0.524427056312561, 'nlp', 1), ('pytorch/ignite', 0.5235216617584229, 'ml-dl', 2), ('squeezeailab/squeezellm', 0.5209859609603882, 'llm', 1), ('llmware-ai/llmware', 0.5209429264068604, 'llm', 1), ('yizhongw/self-instruct', 0.5196613073348999, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5180608034133911, 'llm', 0), ('allenai/allennlp', 0.5176029801368713, 'nlp', 2), ('nvidia/tensorrt-llm', 0.5172522068023682, 'viz', 1), ('huawei-noah/pretrained-language-model', 0.5153259038925171, 'nlp', 1), ('jonasgeiping/cramming', 0.514919102191925, 'nlp', 1), ('keras-team/keras-nlp', 0.5128912329673767, 'nlp', 1), ('iryna-kondr/scikit-llm', 0.5123019814491272, 'llm', 2), ('reasoning-machines/pal', 0.5115619897842407, 'llm', 1), ('lupantech/chameleon-llm', 0.509954571723938, 'llm', 2), ('ggerganov/ggml', 0.5078336596488953, 'ml', 0), ('koaning/scikit-lego', 0.5066888928413391, 'ml', 0), ('eleutherai/the-pile', 0.5063433647155762, 'data', 0), ('salesforce/blip', 0.5060290694236755, 'diffusion', 0), ('mrdbourke/pytorch-deep-learning', 0.503092348575592, 'study', 2), ('tensorflow/tensor2tensor', 0.5030723810195923, 'ml', 1), ('unstructured-io/unstructured-inference', 0.5030722618103027, 'data', 0), ('ludwig-ai/ludwig', 0.5029340386390686, 'ml-ops', 2), ('togethercomputer/redpajama-data', 0.5022752285003662, 'llm', 0), ('d2l-ai/d2l-en', 0.5011979341506958, 'study', 2), ('artidoro/qlora', 0.5009582042694092, 'llm', 1), ('stanfordnlp/dspy', 0.5005626082420349, 'llm', 0), ('titanml/takeoff', 0.5003492832183838, 'llm', 1)] | 38 | 3 | null | 14.75 | 43 | 29 | 10 | 1 | 3 | 6 | 3 | 43 | 48 | 90 | 1.1 | 67 |
1,166 | llm | https://github.com/lvwerra/trl | [] | null | [] | [] | null | null | null | lvwerra/trl | trl | 7,051 | 803 | 67 | Python | http://hf.co/docs/trl | Train transformer language models with reinforcement learning. | lvwerra | 2024-01-14 | 2020-03-27 | 200 | 35.154558 | https://avatars.githubusercontent.com/u/25720743?v=4 | Train transformer language models with reinforcement learning. | [] | [] | 2024-01-12 | [('bigscience-workshop/megatron-deepspeed', 0.6662755608558655, 'llm', 0), ('microsoft/megatron-deepspeed', 0.6662755608558655, 'llm', 0), ('kzl/decision-transformer', 0.5943164229393005, 'ml-rl', 0), ('huggingface/transformers', 0.5739136338233948, 'nlp', 0), ('eleutherai/knowledge-neurons', 0.5679098963737488, 'ml-interpretability', 0), ('thilinarajapakse/simpletransformers', 0.5451595783233643, 'nlp', 0), ('hazyresearch/h3', 0.5428241491317749, 'llm', 0), ('nvidia/megatron-lm', 0.5321753025054932, 'llm', 0), ('jonasgeiping/cramming', 0.5296485424041748, 'nlp', 0), ('facebookresearch/shepherd', 0.5294312834739685, 'llm', 0), ('huggingface/text-generation-inference', 0.523781955242157, 'llm', 0), ('nvlabs/prismer', 0.509940505027771, 'diffusion', 0), ('deepset-ai/farm', 0.5094181299209595, 'nlp', 0), ('ai21labs/lm-evaluation', 0.5060834288597107, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5007656812667847, 'llm', 0), ('mit-han-lab/streaming-llm', 0.5007056593894958, 'llm', 0)] | 133 | 5 | null | 8.81 | 452 | 370 | 46 | 0 | 24 | 6 | 24 | 452 | 1,328 | 90 | 2.9 | 67 |
1,638 | llm | https://github.com/mistralai/mistral-src | [] | null | [] | [] | null | null | null | mistralai/mistral-src | mistral-src | 6,753 | 509 | 81 | Jupyter Notebook | https://mistral.ai/ | Reference implementation of Mistral AI 7B v0.1 model. | mistralai | 2024-01-14 | 2023-09-27 | 17 | 378.168 | https://avatars.githubusercontent.com/u/132372032?v=4 | Reference implementation of Mistral AI 7B v0.1 model. | ['llm', 'llm-inference', 'mistralai'] | ['llm', 'llm-inference', 'mistralai'] | 2023-12-13 | [] | 13 | 6 | null | 0.62 | 86 | 21 | 4 | 1 | 0 | 0 | 0 | 86 | 70 | 90 | 0.8 | 67 |
1,826 | llm | https://github.com/langchain-ai/opengpts | ['assistant', 'api'] | An open source effort to create a similar experience to OpenAI's GPTs and Assistants API. | [] | [] | null | null | null | langchain-ai/opengpts | opengpts | 5,104 | 584 | 54 | Rich Text Format | null | null | langchain-ai | 2024-01-13 | 2023-11-04 | 12 | 410.666667 | https://avatars.githubusercontent.com/u/126733545?v=4 | An open source effort to create a similar experience to OpenAI's GPTs and Assistants API. | [] | ['api', 'assistant'] | 2024-01-02 | [('openai/openai-cookbook', 0.7003576159477234, 'ml', 0), ('openai/openai-python', 0.6509252190589905, 'util', 0), ('shishirpatil/gorilla', 0.6241956353187561, 'llm', 1), ('xtekky/gpt4free', 0.5756799578666687, 'llm', 0), ('fastai/ghapi', 0.5734665393829346, 'util', 0), ('minimaxir/gpt-2-simple', 0.5654781460762024, 'llm', 0), ('laion-ai/open-assistant', 0.5428431034088135, 'llm', 1), ('linksoul-ai/autoagents', 0.5377379655838013, 'llm', 0), ('run-llama/rags', 0.5282418131828308, 'llm', 0), ('opengenerativeai/genossgpt', 0.5244327783584595, 'llm', 1), ('vitalik/django-ninja', 0.5144355297088623, 'web', 0), ('torantulino/auto-gpt', 0.5114303231239319, 'llm', 0), ('assafelovic/gpt-researcher', 0.511093020439148, 'llm', 0), ('openai/tiktoken', 0.5110874176025391, 'nlp', 0), ('prefecthq/marvin', 0.507490336894989, 'nlp', 0), ('lucidrains/toolformer-pytorch', 0.5033729672431946, 'llm', 0)] | 5 | 2 | null | 1.77 | 127 | 71 | 2 | 0 | 0 | 0 | 0 | 127 | 178 | 90 | 1.4 | 67 |
1,396 | llm | https://github.com/lightning-ai/lit-gpt | ['fine-tuning', 'quantization', 'nanogpt'] | null | [] | [] | 1 | null | null | lightning-ai/lit-gpt | lit-gpt | 4,759 | 485 | 60 | Python | null | Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. | lightning-ai | 2024-01-13 | 2023-05-04 | 38 | 122.926199 | https://avatars.githubusercontent.com/u/58386951?v=4 | Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. | [] | ['fine-tuning', 'nanogpt', 'quantization'] | 2024-01-12 | [('lightning-ai/lit-llama', 0.721184253692627, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.6060934066772461, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5745608806610107, 'perf', 0), ('vllm-project/vllm', 0.5720106959342957, 'llm', 0), ('microsoft/llmlingua', 0.5566024780273438, 'llm', 0), ('run-llama/llama-hub', 0.5486422181129456, 'data', 0), ('opengvlab/omniquant', 0.5481755137443542, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5436835289001465, 'llm', 1), ('bentoml/openllm', 0.5373291373252869, 'ml-ops', 1), ('bigscience-workshop/petals', 0.5297286510467529, 'data', 0), ('artidoro/qlora', 0.5197663903236389, 'llm', 0), ('tigerlab-ai/tiger', 0.5195765495300293, 'llm', 1), ('bobazooba/xllm', 0.5175870656967163, 'llm', 0), ('microsoft/semantic-kernel', 0.5075657367706299, 'llm', 0), ('iryna-kondr/scikit-llm', 0.5048611164093018, 'llm', 0), ('predibase/lorax', 0.5018265247344971, 'llm', 1), ('eugeneyan/open-llms', 0.501139223575592, 'study', 0)] | 54 | 6 | null | 12.56 | 338 | 238 | 8 | 0 | 0 | 0 | 0 | 337 | 441 | 90 | 1.3 | 67 |
1,337 | nlp | https://github.com/prefecthq/marvin | [] | null | [] | [] | null | null | null | prefecthq/marvin | marvin | 4,193 | 412 | 36 | Python | https://askmarvin.ai | β¨ Build AI interfaces that spark joy | prefecthq | 2024-01-14 | 2023-03-10 | 46 | 90.033742 | https://avatars.githubusercontent.com/u/39270919?v=4 | β¨ Build AI interfaces that spark joy | ['agents', 'ai', 'ai-functions', 'ambient-ai', 'chatbots', 'gpt', 'llm', 'nli', 'openai'] | ['agents', 'ai', 'ai-functions', 'ambient-ai', 'chatbots', 'gpt', 'llm', 'nli', 'openai'] | 2024-01-13 | [('antonosika/gpt-engineer', 0.7385191917419434, 'llm', 2), ('cheshire-cat-ai/core', 0.7232251167297363, 'llm', 2), ('mindsdb/mindsdb', 0.7208438515663147, 'data', 3), ('embedchain/embedchain', 0.6899540424346924, 'llm', 3), ('lastmile-ai/aiconfig', 0.6677407622337341, 'util', 2), ('krohling/bondai', 0.6641014814376831, 'llm', 1), ('microsoft/promptflow', 0.6454984545707703, 'llm', 3), ('microsoft/lmops', 0.6434080600738525, 'llm', 2), ('chatarena/chatarena', 0.6427308917045593, 'llm', 1), ('microsoft/generative-ai-for-beginners', 0.6387981176376343, 'study', 3), ('smol-ai/developer', 0.6331506967544556, 'llm', 1), ('transformeroptimus/superagi', 0.6271318197250366, 'llm', 4), ('operand/agency', 0.6231884956359863, 'llm', 3), ('sweepai/sweep', 0.6178321838378906, 'llm', 2), ('run-llama/rags', 0.6145691275596619, 'llm', 2), ('mlc-ai/mlc-llm', 0.6106210350990295, 'llm', 1), ('minimaxir/simpleaichat', 0.6048039197921753, 'llm', 1), ('rasahq/rasa', 0.6008431315422058, 'llm', 1), ('pathwaycom/llm-app', 0.5963694453239441, 'llm', 1), ('bentoml/bentoml', 0.591640830039978, 'ml-ops', 1), ('thilinarajapakse/simpletransformers', 0.5893362760543823, 'nlp', 0), ('oegedijk/explainerdashboard', 0.584237813949585, 'ml-interpretability', 0), ('microsoft/semantic-kernel', 0.583898663520813, 'llm', 3), ('facebookresearch/habitat-lab', 0.5811783671379089, 'sim', 1), ('rcgai/simplyretrieve', 0.5794979929924011, 'llm', 0), ('larsbaunwall/bricky', 0.577139675617218, 'llm', 2), ('pytorchlightning/pytorch-lightning', 0.5638337135314941, 'ml-dl', 1), ('deeppavlov/deeppavlov', 0.5636438131332397, 'nlp', 1), ('togethercomputer/openchatkit', 0.5622385144233704, 'nlp', 0), ('humanoidagents/humanoidagents', 0.5612106919288635, 'sim', 1), ('nvidia/nemo', 0.560585081577301, 'nlp', 0), ('microsoft/autogen', 0.5600186586380005, 'llm', 1), ('lupantech/chameleon-llm', 0.5581182837486267, 'llm', 3), ('jina-ai/jina', 0.5576962828636169, 'ml', 0), ('modularml/mojo', 0.5523964166641235, 'util', 1), ('nomic-ai/gpt4all', 0.5499098896980286, 'llm', 0), ('google/dopamine', 0.547942042350769, 'ml-rl', 1), ('torantulino/auto-gpt', 0.5470284223556519, 'llm', 2), ('googlecloudplatform/vertex-ai-samples', 0.5464761853218079, 'ml', 1), ('lucidrains/toolformer-pytorch', 0.5462851524353027, 'llm', 0), ('oliveirabruno01/babyagi-asi', 0.5443987846374512, 'llm', 1), ('aimhubio/aim', 0.541201114654541, 'ml-ops', 1), ('unity-technologies/ml-agents', 0.5411503911018372, 'ml-rl', 0), ('lm-sys/fastchat', 0.5400978922843933, 'llm', 0), ('avaiga/taipy', 0.5397293567657471, 'data', 0), ('xtekky/gpt4free', 0.536582887172699, 'llm', 3), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5360046029090881, 'llm', 0), ('mnotgod96/appagent', 0.5343064665794373, 'llm', 1), ('explosion/thinc', 0.5329232811927795, 'ml-dl', 1), ('oneil512/insight', 0.5314114093780518, 'ml', 3), ('pythagora-io/gpt-pilot', 0.5274754762649536, 'llm', 1), ('deepset-ai/haystack', 0.524747908115387, 'llm', 1), ('killianlucas/open-interpreter', 0.5231456756591797, 'llm', 0), ('microsoft/promptcraft-robotics', 0.5221617817878723, 'sim', 1), ('kitao/pyxel', 0.520916759967804, 'gamedev', 0), ('google-research/language', 0.5198028087615967, 'nlp', 0), ('activeloopai/deeplake', 0.5178278088569641, 'ml-ops', 2), ('minimaxir/aitextgen', 0.5176252126693726, 'llm', 0), ('hwchase17/langchain', 0.5155816078186035, 'llm', 0), ('luodian/otter', 0.5130387544631958, 'llm', 0), ('openai/openai-cookbook', 0.5121986269950867, 'ml', 1), ('intel/intel-extension-for-transformers', 0.5106049180030823, 'perf', 0), ('gventuri/pandas-ai', 0.5097314715385437, 'pandas', 2), ('mlflow/mlflow', 0.5080140233039856, 'ml-ops', 1), ('langchain-ai/opengpts', 0.507490336894989, 'llm', 0), ('eugeneyan/obsidian-copilot', 0.5069007277488708, 'llm', 1), ('aiwaves-cn/agents', 0.506673276424408, 'nlp', 1), ('guardrails-ai/guardrails', 0.5055996179580688, 'llm', 3), ('databrickslabs/dolly', 0.5005607008934021, 'llm', 1), ('noahshinn/reflexion', 0.5003121495246887, 'llm', 2)] | 29 | 5 | null | 33.62 | 136 | 89 | 10 | 0 | 43 | 52 | 43 | 136 | 92 | 90 | 0.7 | 67 |
1,231 | llm | https://github.com/karpathy/nanogpt | ['nanogpt'] | null | [] | [] | null | null | null | karpathy/nanogpt | nanoGPT | 28,200 | 4,040 | 320 | Python | null | The simplest, fastest repository for training/finetuning medium-sized GPTs. | karpathy | 2024-01-14 | 2022-12-28 | 56 | 495.979899 | null | The simplest, fastest repository for training/finetuning medium-sized GPTs. | [] | ['nanogpt'] | 2023-06-22 | [('karpathy/mingpt', 0.5497898459434509, 'llm', 0), ('vision-cair/minigpt-4', 0.5487928986549377, 'llm', 0), ('farizrahman4u/loopgpt', 0.5409718155860901, 'llm', 0), ('openai/gpt-2-output-dataset', 0.5051628351211548, 'llm', 0), ('eleutherai/gpt-neo', 0.5039609670639038, 'llm', 0)] | 31 | 3 | null | 1.44 | 53 | 14 | 13 | 7 | 0 | 0 | 0 | 52 | 43 | 90 | 0.8 | 66 |
408 | perf | https://github.com/google/flatbuffers | [] | null | [] | [] | null | null | null | google/flatbuffers | flatbuffers | 21,620 | 3,213 | 641 | C++ | https://flatbuffers.dev/ | FlatBuffers: Memory Efficient Serialization Library | google | 2024-01-14 | 2014-05-19 | 506 | 42.715213 | https://avatars.githubusercontent.com/u/1342004?v=4 | FlatBuffers: Memory Efficient Serialization Library | ['c', 'c-plus-plus', 'c-sharp', 'cross-platform', 'flatbuffers', 'go', 'grpc', 'java', 'javascript', 'json-parser', 'marshalling', 'mmap', 'protobuf', 'rpc', 'rust', 'serialization', 'serialization-library', 'typescript', 'zero-copy'] | ['c', 'c-plus-plus', 'c-sharp', 'cross-platform', 'flatbuffers', 'go', 'grpc', 'java', 'javascript', 'json-parser', 'marshalling', 'mmap', 'protobuf', 'rpc', 'rust', 'serialization', 'serialization-library', 'typescript', 'zero-copy'] | 2023-12-19 | [('yukinarit/pyserde', 0.6145598292350769, 'util', 1), ('pylons/colander', 0.5039762258529663, 'util', 1)] | 670 | 5 | null | 3.85 | 184 | 102 | 118 | 1 | 6 | 4 | 6 | 184 | 252 | 90 | 1.4 | 66 |
188 | ml-interpretability | https://github.com/slundberg/shap | [] | null | [] | [] | null | null | null | slundberg/shap | shap | 20,940 | 3,099 | 252 | Jupyter Notebook | https://shap.readthedocs.io | A game theoretic approach to explain the output of any machine learning model. | slundberg | 2024-01-14 | 2016-11-22 | 375 | 55.84 | https://avatars.githubusercontent.com/u/60805229?v=4 | A game theoretic approach to explain the output of any machine learning model. | ['deep-learning', 'explainability', 'gradient-boosting', 'interpretability', 'machine-learning', 'shap', 'shapley'] | ['deep-learning', 'explainability', 'gradient-boosting', 'interpretability', 'machine-learning', 'shap', 'shapley'] | 2024-01-09 | [('maif/shapash', 0.67304927110672, 'ml', 4), ('seldonio/alibi', 0.6683449745178223, 'ml-interpretability', 2), ('marcotcr/lime', 0.6387524604797363, 'ml-interpretability', 0), ('interpretml/interpret', 0.5977214574813843, 'ml-interpretability', 4), ('linkedin/fasttreeshap', 0.5951489806175232, 'ml', 3), ('xplainable/xplainable', 0.5842406153678894, 'ml-interpretability', 2), ('oegedijk/explainerdashboard', 0.5450636148452759, 'ml-interpretability', 1), ('csinva/imodels', 0.5444343090057373, 'ml', 2), ('mosaicml/composer', 0.5438055396080017, 'ml-dl', 2), ('unity-technologies/ml-agents', 0.5413389205932617, 'ml-rl', 2), ('pair-code/lit', 0.532273530960083, 'ml-interpretability', 1), ('ddbourgin/numpy-ml', 0.5084296464920044, 'ml', 2), ('tensorflow/lucid', 0.5016194581985474, 'ml-interpretability', 2)] | 229 | 4 | null | 5.5 | 691 | 90 | 87 | 0 | 4 | 7 | 4 | 690 | 688 | 90 | 1 | 66 |
1,053 | ml | https://github.com/microsoft/lightgbm | [] | null | [] | [] | null | null | null | microsoft/lightgbm | LightGBM | 15,787 | 3,793 | 437 | C++ | https://lightgbm.readthedocs.io/en/latest/ | A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. | microsoft | 2024-01-14 | 2016-08-05 | 390 | 40.420263 | https://avatars.githubusercontent.com/u/6154722?v=4 | A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. | ['data-mining', 'decision-trees', 'distributed', 'gbdt', 'gbm', 'gbrt', 'gradient-boosting', 'kaggle', 'lightgbm', 'machine-learning', 'microsoft', 'parallel', 'r'] | ['data-mining', 'decision-trees', 'distributed', 'gbdt', 'gbm', 'gbrt', 'gradient-boosting', 'kaggle', 'lightgbm', 'machine-learning', 'microsoft', 'parallel', 'r'] | 2024-01-12 | [('dmlc/xgboost', 0.8464224338531494, 'ml', 4), ('catboost/catboost', 0.8396483659744263, 'ml', 8)] | 295 | 5 | null | 4.75 | 338 | 259 | 91 | 0 | 3 | 5 | 3 | 339 | 598 | 90 | 1.8 | 66 |
1,440 | llm | https://github.com/karpathy/llama2.c | ['llama', 'language-model'] | null | [] | [] | null | null | null | karpathy/llama2.c | llama2.c | 13,860 | 1,471 | 159 | C | null | Inference Llama 2 in one file of pure C | karpathy | 2024-01-14 | 2023-07-23 | 27 | 507.958115 | null | Inference Llama 2 in one file of pure C | [] | ['language-model', 'llama'] | 2023-10-09 | [('facebookresearch/llama', 0.8788975477218628, 'llm', 2), ('tairov/llama2.mojo', 0.8035979270935059, 'llm', 1), ('facebookresearch/codellama', 0.7492680549621582, 'llm', 2), ('facebookresearch/llama-recipes', 0.7288556098937988, 'llm', 2), ('microsoft/llama-2-onnx', 0.6777373552322388, 'llm', 2), ('abetlen/llama-cpp-python', 0.6725909113883972, 'llm', 2), ('tloen/alpaca-lora', 0.5766897201538086, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.5627032518386841, 'llm', 0), ('cg123/mergekit', 0.541799783706665, 'llm', 1), ('hao-ai-lab/lookaheaddecoding', 0.5412218570709229, 'llm', 0), ('openlm-research/open_llama', 0.5405749678611755, 'llm', 2), ('ggerganov/llama.cpp', 0.5367782711982727, 'llm', 2), ('jzhang38/tinyllama', 0.5350930094718933, 'llm', 2), ('juncongmoo/pyllama', 0.5219447016716003, 'llm', 0), ('run-llama/llama-lab', 0.5159832835197449, 'llm', 2), ('zrrskywalker/llama-adapter', 0.5048466920852661, 'llm', 2)] | 81 | 1 | null | 6.5 | 74 | 11 | 6 | 3 | 0 | 0 | 0 | 74 | 51 | 90 | 0.7 | 66 |
123 | ml-ops | https://github.com/iterative/dvc | [] | null | [] | [] | null | null | null | iterative/dvc | dvc | 12,755 | 1,141 | 137 | Python | https://dvc.org | π¦ ML Experiments Management with Git | iterative | 2024-01-13 | 2017-03-04 | 360 | 35.388426 | https://avatars.githubusercontent.com/u/39572954?v=4 | π¦ ML Experiments Management with Git | ['ai', 'collaboration', 'data-science', 'data-version-control', 'developer-tools', 'git', 'machine-learning', 'reproducibility'] | ['ai', 'collaboration', 'data-science', 'data-version-control', 'developer-tools', 'git', 'machine-learning', 'reproducibility'] | 2024-01-12 | [('netflix/metaflow', 0.6912345886230469, 'ml-ops', 3), ('allegroai/clearml', 0.618588924407959, 'ml-ops', 2), ('wandb/client', 0.6113179922103882, 'ml', 4), ('aimhubio/aim', 0.5769718885421753, 'ml-ops', 3), ('pythagora-io/gpt-pilot', 0.5759281516075134, 'llm', 2), ('sweepai/sweep', 0.5702275633811951, 'llm', 2), ('polyaxon/polyaxon', 0.5695563554763794, 'ml-ops', 2), ('bentoml/bentoml', 0.5435565710067749, 'ml-ops', 2), ('googlecloudplatform/vertex-ai-samples', 0.5397675633430481, 'ml', 2), ('mindsdb/mindsdb', 0.5321820974349976, 'data', 2), ('lastmile-ai/aiconfig', 0.522969663143158, 'util', 2), ('avaiga/taipy', 0.5210314989089966, 'data', 1), ('google-research/language', 0.5162245631217957, 'nlp', 1), ('microsoft/promptflow', 0.514451265335083, 'llm', 1), ('alirezadir/machine-learning-interview-enlightener', 0.5138351917266846, 'study', 2), ('google-research/google-research', 0.5124830603599548, 'ml', 2), ('feast-dev/feast', 0.5111587047576904, 'ml-ops', 2), ('determined-ai/determined', 0.5081852674484253, 'ml-ops', 2), ('ploomber/ploomber', 0.5037345886230469, 'ml-ops', 2), ('google/ml-metadata', 0.5009445548057556, 'ml-ops', 0), ('mlflow/mlflow', 0.5006384253501892, 'ml-ops', 2)] | 290 | 2 | null | 15.94 | 347 | 271 | 84 | 0 | 101 | 76 | 101 | 347 | 751 | 90 | 2.2 | 66 |
514 | typing | https://github.com/microsoft/pyright | ['typechecker', 'code-quality'] | null | [] | [] | null | null | null | microsoft/pyright | pyright | 11,459 | 1,267 | 113 | Python | null | Static Type Checker for Python | microsoft | 2024-01-14 | 2019-03-12 | 255 | 44.937255 | https://avatars.githubusercontent.com/u/6154722?v=4 | Static Type Checker for Python | [] | ['code-quality', 'typechecker'] | 2024-01-14 | [('agronholm/typeguard', 0.9137517213821411, 'typing', 2), ('python/mypy', 0.8244960904121399, 'typing', 2), ('google/pytype', 0.8127192258834839, 'typing', 2), ('facebook/pyre-check', 0.7650810480117798, 'typing', 2), ('instagram/monkeytype', 0.7293500900268555, 'typing', 1), ('python/typeshed', 0.6651108264923096, 'typing', 1), ('patrick-kidger/torchtyping', 0.5727251172065735, 'typing', 0), ('pycqa/mccabe', 0.5418702960014343, 'util', 0), ('jendrikseipp/vulture', 0.536612331867218, 'util', 1), ('rubik/radon', 0.533168375492096, 'util', 0), ('landscapeio/prospector', 0.5327200293540955, 'util', 0), ('google/yapf', 0.5311009287834167, 'util', 1), ('grantjenks/blue', 0.529589056968689, 'util', 1), ('pycqa/pycodestyle', 0.5176783204078674, 'util', 0), ('pycqa/pyflakes', 0.511178195476532, 'util', 0), ('pydantic/pydantic', 0.5103999376296997, 'util', 0), ('psf/black', 0.5090447068214417, 'util', 1)] | 103 | 1 | null | 26.13 | 789 | 758 | 59 | 0 | 57 | 88 | 57 | 787 | 1,674 | 90 | 2.1 | 66 |
225 | util | https://github.com/pyodide/pyodide | ['cpython', 'wasm', 'emscripten', 'webassembly'] | null | [] | [] | null | null | null | pyodide/pyodide | pyodide | 10,896 | 738 | 129 | Python | https://pyodide.org/en/stable/ | Pyodide is a Python distribution for the browser and Node.js based on WebAssembly | pyodide | 2024-01-14 | 2018-02-23 | 309 | 35.197047 | https://avatars.githubusercontent.com/u/77002075?v=4 | Pyodide is a Python distribution for the browser and Node.js based on WebAssembly | ['webassembly'] | ['cpython', 'emscripten', 'wasm', 'webassembly'] | 2024-01-13 | [('pyodide/micropip', 0.7593028545379639, 'util', 1), ('webpy/webpy', 0.6373624205589294, 'web', 0), ('bottlepy/bottle', 0.6117225289344788, 'web', 0), ('cherrypy/cherrypy', 0.5807443857192993, 'web', 0), ('libtcod/python-tcod', 0.5775824785232544, 'gamedev', 0), ('pypy/pypy', 0.5725159645080566, 'util', 1), ('jupyterlite/jupyterlite', 0.5671476721763611, 'jupyter', 2), ('pallets/flask', 0.556867241859436, 'web', 0), ('masoniteframework/masonite', 0.5539262294769287, 'web', 0), ('seleniumbase/seleniumbase', 0.540057897567749, 'testing', 0), ('pylons/pyramid', 0.5352792739868164, 'web', 0), ('reactive-python/reactpy', 0.5306482911109924, 'web', 0), ('scrapy/scrapy', 0.5298803448677063, 'data', 0), ('r0x0r/pywebview', 0.5263348817825317, 'gui', 0), ('pyscript/pyscript', 0.5230824947357178, 'web', 3), ('microsoft/playwright-python', 0.5146863460540771, 'testing', 0), ('klen/muffin', 0.5121115446090698, 'web', 0), ('hoffstadt/dearpygui', 0.5109636187553406, 'gui', 0), ('pyglet/pyglet', 0.5096766948699951, 'gamedev', 0), ('reflex-dev/reflex', 0.5090579986572266, 'web', 0), ('clips/pattern', 0.5079214572906494, 'nlp', 0), ('pytest-dev/pytest-bdd', 0.5067077279090881, 'testing', 0), ('pyo3/maturin', 0.504960834980011, 'util', 1)] | 207 | 5 | null | 9.38 | 180 | 113 | 72 | 0 | 12 | 13 | 12 | 180 | 385 | 90 | 2.1 | 66 |
29 | ml-ops | https://github.com/great-expectations/great_expectations | [] | null | [] | [] | null | null | null | great-expectations/great_expectations | great_expectations | 9,157 | 1,443 | 82 | Python | https://docs.greatexpectations.io/ | Always know what to expect from your data. | great-expectations | 2024-01-13 | 2017-09-11 | 333 | 27.486707 | https://avatars.githubusercontent.com/u/31670619?v=4 | Always know what to expect from your data. | ['cleandata', 'data-engineering', 'data-profilers', 'data-profiling', 'data-quality', 'data-science', 'data-unit-tests', 'datacleaner', 'datacleaning', 'dataquality', 'dataunittest', 'eda', 'exploratory-analysis', 'exploratory-data-analysis', 'exploratorydataanalysis', 'mlops', 'pipeline', 'pipeline-debt', 'pipeline-testing', 'pipeline-tests'] | ['cleandata', 'data-engineering', 'data-profilers', 'data-profiling', 'data-quality', 'data-science', 'data-unit-tests', 'datacleaner', 'datacleaning', 'dataquality', 'dataunittest', 'eda', 'exploratory-analysis', 'exploratory-data-analysis', 'exploratorydataanalysis', 'mlops', 'pipeline', 'pipeline-debt', 'pipeline-testing', 'pipeline-tests'] | 2024-01-12 | [('ydataai/ydata-profiling', 0.606023907661438, 'pandas', 5), ('hi-primus/optimus', 0.6027732491493225, 'ml-ops', 2), ('mage-ai/mage-ai', 0.5621156692504883, 'ml-ops', 3), ('ploomber/ploomber', 0.5521277785301208, 'ml-ops', 3), ('datafold/data-diff', 0.5429127216339111, 'data', 4), ('polyaxon/datatile', 0.5381271839141846, 'pandas', 4), ('ydataai/ydata-quality', 0.5358034372329712, 'data', 0), ('unionai-oss/pandera', 0.5351150035858154, 'pandas', 0), ('feast-dev/feast', 0.5238198041915894, 'ml-ops', 4), ('orchest/orchest', 0.5189650058746338, 'ml-ops', 1), ('dagworks-inc/hamilton', 0.5179693102836609, 'ml-ops', 3), ('google/ml-metadata', 0.5165597200393677, 'ml-ops', 0), ('airbytehq/airbyte', 0.5163770914077759, 'data', 2), ('dbt-labs/dbt-core', 0.5088808536529541, 'ml-ops', 0), ('krzjoa/awesome-python-data-science', 0.5083687901496887, 'study', 1), ('linealabs/lineapy', 0.5049693584442139, 'jupyter', 0), ('whylabs/whylogs', 0.5034822821617126, 'util', 3), ('meltano/meltano', 0.5034080147743225, 'ml-ops', 1)] | 423 | 3 | null | 45.29 | 909 | 826 | 77 | 0 | 55 | 44 | 55 | 907 | 922 | 90 | 1 | 66 |
117 | ml-ops | https://github.com/kedro-org/kedro | [] | null | [] | [] | null | From: https://github.com/quantumblacklabs/kedro | null | kedro-org/kedro | kedro | 9,091 | 860 | 107 | Python | https://kedro.org | Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular. | kedro-org | 2024-01-14 | 2019-04-18 | 249 | 36.405606 | https://avatars.githubusercontent.com/u/93382166?v=4 | Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular. | ['experiment-tracking', 'kedro', 'machine-learning', 'machine-learning-engineering', 'mlops', 'pipeline'] | ['experiment-tracking', 'kedro', 'machine-learning', 'machine-learning-engineering', 'mlops', 'pipeline'] | 2024-01-12 | [('kedro-org/kedro-viz', 0.7322895526885986, 'ml-ops', 2), ('getindata/kedro-kubeflow', 0.660918653011322, 'ml-ops', 2), ('meltano/meltano', 0.5286129117012024, 'ml-ops', 0), ('kubeflow-kale/kale', 0.5225927233695984, 'ml-ops', 1), ('ploomber/ploomber', 0.5186499357223511, 'ml-ops', 2), ('mage-ai/mage-ai', 0.5148924589157104, 'ml-ops', 2), ('dagster-io/dagster', 0.5058962106704712, 'ml-ops', 1), ('polyaxon/polyaxon', 0.5058719515800476, 'ml-ops', 2), ('zenml-io/zenml', 0.5034431219100952, 'ml-ops', 2)] | 218 | 4 | null | 9.52 | 583 | 417 | 58 | 0 | 12 | 10 | 12 | 583 | 1,135 | 90 | 1.9 | 66 |
1,368 | llm | https://github.com/shishirpatil/gorilla | [] | null | [] | [] | null | null | null | shishirpatil/gorilla | gorilla | 8,848 | 682 | 97 | Python | https://gorilla.cs.berkeley.edu/ | Gorilla: An API store for LLMs | shishirpatil | 2024-01-14 | 2023-05-19 | 36 | 241.9375 | null | Gorilla: An API store for LLMs | ['api', 'api-documentation', 'chatgpt', 'claude-api', 'gpt-4-api', 'llm', 'openai-api', 'openai-functions'] | ['api', 'api-documentation', 'chatgpt', 'claude-api', 'gpt-4-api', 'llm', 'openai-api', 'openai-functions'] | 2023-11-20 | [('berriai/litellm', 0.7173708081245422, 'llm', 1), ('openai/openai-cookbook', 0.6725669503211975, 'ml', 1), ('opengenerativeai/genossgpt', 0.6697072982788086, 'llm', 2), ('mmabrouk/chatgpt-wrapper', 0.6682367324829102, 'llm', 2), ('zilliztech/gptcache', 0.6505623459815979, 'llm', 2), ('run-llama/rags', 0.6374510526657104, 'llm', 2), ('xtekky/gpt4free', 0.6333321332931519, 'llm', 2), ('alphasecio/langchain-examples', 0.6303489804267883, 'llm', 1), ('langchain-ai/opengpts', 0.6241956353187561, 'llm', 1), ('openai/openai-python', 0.6225490570068359, 'util', 0), ('chainlit/chainlit', 0.6185116171836853, 'llm', 2), ('pathwaycom/llm-app', 0.6179982423782349, 'llm', 1), ('nomic-ai/gpt4all', 0.6152714490890503, 'llm', 0), ('microsoft/semantic-kernel', 0.612429678440094, 'llm', 1), ('microsoft/promptflow', 0.6032128930091858, 'llm', 2), ('dylanhogg/llmgraph', 0.5875014662742615, 'ml', 2), ('embedchain/embedchain', 0.5869289636611938, 'llm', 2), ('vitalik/django-ninja', 0.5843652486801147, 'web', 0), ('deepset-ai/haystack', 0.5841556787490845, 'llm', 1), ('hwchase17/langchain', 0.5784041285514832, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5774163603782654, 'perf', 0), ('eugeneyan/open-llms', 0.5759145021438599, 'study', 1), ('deep-diver/llm-as-chatbot', 0.5617109537124634, 'llm', 0), ('ajndkr/lanarky', 0.5609325766563416, 'llm', 0), ('h2oai/h2o-llmstudio', 0.5525274872779846, 'llm', 2), ('hugapi/hug', 0.5522815585136414, 'util', 0), ('tiangolo/fastapi', 0.5488146543502808, 'web', 1), ('fastai/ghapi', 0.5438264012336731, 'util', 0), ('tigerlab-ai/tiger', 0.5373891592025757, 'llm', 1), ('jerryjliu/llama_index', 0.5362586975097656, 'llm', 1), ('microsoft/autogen', 0.5344410538673401, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.5339228510856628, 'llm', 0), ('mlc-ai/web-llm', 0.533381462097168, 'llm', 2), ('salesforce/codet5', 0.5298489332199097, 'nlp', 0), ('young-geng/easylm', 0.5281785130500793, 'llm', 0), ('bobazooba/xllm', 0.5277217626571655, 'llm', 2), ('vllm-project/vllm', 0.5265129208564758, 'llm', 1), ('bigscience-workshop/petals', 0.5255513191223145, 'data', 0), ('microsoft/promptcraft-robotics', 0.5253349542617798, 'sim', 2), ('tiangolo/full-stack-fastapi-postgresql', 0.5247654914855957, 'template', 0), ('googleapis/google-api-python-client', 0.524009108543396, 'util', 0), ('snyk-labs/pysnyk', 0.5202717185020447, 'security', 1), ('mooler0410/llmspracticalguide', 0.5199465751647949, 'study', 0), ('farizrahman4u/loopgpt', 0.5184142589569092, 'llm', 1), ('starlite-api/starlite', 0.5183838605880737, 'web', 1), ('run-llama/llama-hub', 0.5163030028343201, 'data', 1), ('salesforce/xgen', 0.5161482691764832, 'llm', 1), ('nebuly-ai/nebullvm', 0.512731671333313, 'perf', 1), ('killianlucas/open-interpreter', 0.5121797323226929, 'llm', 1), ('confident-ai/deepeval', 0.5115599036216736, 'testing', 2), ('skypilot-org/skypilot', 0.5099743008613586, 'llm', 0), ('citadel-ai/langcheck', 0.5088066458702087, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5080721378326416, 'llm', 1), ('bentoml/openllm', 0.5051870942115784, 'ml-ops', 1), ('larsbaunwall/bricky', 0.5044655799865723, 'llm', 0), ('openai/tiktoken', 0.5037037134170532, 'nlp', 1), ('hegelai/prompttools', 0.5024935603141785, 'llm', 0), ('pomponchik/instld', 0.5003833174705505, 'util', 0), ('falconry/falcon', 0.500187873840332, 'web', 1)] | 15 | 6 | null | 0.75 | 27 | 13 | 8 | 2 | 1 | 2 | 1 | 27 | 39 | 90 | 1.4 | 66 |
533 | nlp | https://github.com/espnet/espnet | [] | null | [] | [] | null | null | null | espnet/espnet | espnet | 7,522 | 2,046 | 179 | Python | https://espnet.github.io/espnet/ | End-to-End Speech Processing Toolkit | espnet | 2024-01-14 | 2017-12-13 | 319 | 23.516749 | https://avatars.githubusercontent.com/u/34493687?v=4 | End-to-End Speech Processing Toolkit | ['chainer', 'deep-learning', 'end-to-end', 'kaldi', 'machine-translation', 'pytorch', 'singing-voice-synthesis', 'speaker-diarization', 'speech-enhancement', 'speech-recognition', 'speech-separation', 'speech-synthesis', 'speech-translation', 'spoken-language-understanding', 'voice-conversion'] | ['chainer', 'deep-learning', 'end-to-end', 'kaldi', 'machine-translation', 'pytorch', 'singing-voice-synthesis', 'speaker-diarization', 'speech-enhancement', 'speech-recognition', 'speech-separation', 'speech-synthesis', 'speech-translation', 'spoken-language-understanding', 'voice-conversion'] | 2024-01-10 | [('speechbrain/speechbrain', 0.822684109210968, 'nlp', 7), ('nvidia/nemo', 0.63554447889328, 'nlp', 5), ('nateshmbhat/pyttsx3', 0.6220706105232239, 'util', 0), ('uberi/speech_recognition', 0.6095865964889526, 'ml', 1), ('huggingface/transformers', 0.5976542234420776, 'nlp', 3), ('m-bain/whisperx', 0.5822861194610596, 'nlp', 1), ('pndurette/gtts', 0.5670027732849121, 'util', 0), ('deeppavlov/deeppavlov', 0.5584684610366821, 'nlp', 1), ('rasahq/rasa', 0.5472486615180969, 'llm', 0), ('huggingface/datasets', 0.5337874889373779, 'nlp', 2), ('spotify/pedalboard', 0.5202059745788574, 'util', 0), ('lucidrains/toolformer-pytorch', 0.5174741744995117, 'llm', 1), ('spotify/basic-pitch', 0.5158132910728455, 'util', 0), ('nvidia/deeplearningexamples', 0.5145514607429504, 'ml-dl', 4), ('open-mmlab/mmediting', 0.5127143859863281, 'ml', 2), ('facebookresearch/seamless_communication', 0.5085058212280273, 'nlp', 0), ('alibaba/easynlp', 0.5063716173171997, 'nlp', 2), ('thilinarajapakse/simpletransformers', 0.5008228421211243, 'nlp', 0)] | 398 | 5 | null | 69.46 | 207 | 108 | 74 | 0 | 4 | 8 | 4 | 207 | 532 | 90 | 2.6 | 66 |
871 | time-series | https://github.com/sktime/sktime | [] | null | [] | [] | 1 | null | null | sktime/sktime | sktime | 7,149 | 1,191 | 102 | Python | https://www.sktime.net | A unified framework for machine learning with time series | sktime | 2024-01-14 | 2018-11-06 | 273 | 26.186813 | https://avatars.githubusercontent.com/u/56396127?v=4 | A unified framework for machine learning with time series | ['data-mining', 'data-science', 'forecasting', 'machine-learning', 'scikit-learn', 'time-series', 'time-series-analysis', 'time-series-classification', 'time-series-regression'] | ['data-mining', 'data-science', 'forecasting', 'machine-learning', 'scikit-learn', 'time-series', 'time-series-analysis', 'time-series-classification', 'time-series-regression'] | 2024-01-13 | [('salesforce/merlion', 0.7518776059150696, 'time-series', 3), ('winedarksea/autots', 0.7021391987800598, 'time-series', 3), ('scikit-learn/scikit-learn', 0.6196394562721252, 'ml', 2), ('blue-yonder/tsfresh', 0.5950053930282593, 'time-series', 2), ('firmai/atspy', 0.5919238924980164, 'time-series', 3), ('alkaline-ml/pmdarima', 0.5908213257789612, 'time-series', 3), ('automl/auto-sklearn', 0.5886750817298889, 'ml', 1), ('unit8co/darts', 0.5841982960700989, 'time-series', 4), ('google/temporian', 0.5772302150726318, 'time-series', 1), ('awslabs/autogluon', 0.5768527984619141, 'ml', 5), ('xplainable/xplainable', 0.5621213912963867, 'ml-interpretability', 2), ('awslabs/gluonts', 0.5607674717903137, 'time-series', 4), ('salesforce/deeptime', 0.5567091107368469, 'time-series', 3), ('tensorflow/tensorflow', 0.5532556176185608, 'ml-dl', 1), ('rasbt/mlxtend', 0.5530063509941101, 'ml', 3), ('aistream-peelout/flow-forecast', 0.5518553256988525, 'time-series', 4), ('nixtla/statsforecast', 0.5418822169303894, 'time-series', 4), ('feast-dev/feast', 0.5417338609695435, 'ml-ops', 2), ('firmai/industry-machine-learning', 0.541723370552063, 'study', 2), ('pycaret/pycaret', 0.5355731844902039, 'ml', 3), ('microsoft/nni', 0.5316794514656067, 'ml', 2), ('facebookresearch/kats', 0.5305997729301453, 'time-series', 1), ('online-ml/river', 0.5300047993659973, 'ml', 2), ('ourownstory/neural_prophet', 0.529460608959198, 'ml', 3), ('linkedin/greykite', 0.5227073431015015, 'ml', 0), ('nccr-itmo/fedot', 0.520081639289856, 'ml-ops', 1), ('mlflow/mlflow', 0.5184756517410278, 'ml-ops', 1), ('microsoft/flaml', 0.5142588019371033, 'ml', 3), ('patchy631/machine-learning', 0.5128931403160095, 'ml', 0), ('koaning/human-learn', 0.5112270712852478, 'data', 2), ('districtdatalabs/yellowbrick', 0.5111024975776672, 'ml', 2), ('gradio-app/gradio', 0.5101883411407471, 'viz', 2), ('microprediction/microprediction', 0.5038242340087891, 'time-series', 1), ('polyaxon/datatile', 0.5024852752685547, 'pandas', 1)] | 315 | 6 | null | 16.44 | 360 | 240 | 63 | 0 | 22 | 12 | 22 | 360 | 796 | 90 | 2.2 | 66 |
1,643 | llm | https://github.com/plachtaa/vall-e-x | [] | null | [] | [] | null | null | null | plachtaa/vall-e-x | VALL-E-X | 6,692 | 638 | 73 | Python | null | An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io | plachtaa | 2024-01-14 | 2023-07-29 | 26 | 253.210811 | null | An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io | ['emotional-speech', 'gpt', 'text-to-speech', 'transformer-architecture', 'tts', 'vall-e', 'voice-clone'] | ['emotional-speech', 'gpt', 'text-to-speech', 'transformer-architecture', 'tts', 'vall-e', 'voice-clone'] | 2023-11-03 | [('neonbjb/tortoise-tts', 0.6283189058303833, 'ml', 1), ('myshell-ai/openvoice', 0.6065437197685242, 'nlp', 3), ('pndurette/gtts', 0.5036769509315491, 'util', 2)] | 9 | 6 | null | 2.25 | 53 | 12 | 6 | 2 | 0 | 0 | 0 | 53 | 90 | 90 | 1.7 | 66 |
1,856 | llm | https://github.com/pytorch-labs/gpt-fast | ['pytorch', 'transformer'] | null | [] | [] | null | null | null | pytorch-labs/gpt-fast | gpt-fast | 4,442 | 465 | 52 | Python | null | Simple and efficient pytorch-native transformer text generation in <1000 LOC of python. | pytorch-labs | 2024-01-14 | 2023-10-17 | 15 | 296.133333 | https://avatars.githubusercontent.com/u/107212512?v=4 | Simple and efficient pytorch-native transformer text generation in <1000 LOC of python. | [] | ['pytorch', 'transformer'] | 2024-01-06 | [('karpathy/mingpt', 0.5887901782989502, 'llm', 0), ('pytorch/data', 0.5759943723678589, 'data', 0), ('huggingface/text-generation-inference', 0.5448298454284668, 'llm', 2), ('nateshmbhat/pyttsx3', 0.537563145160675, 'util', 0), ('lucidrains/dalle2-pytorch', 0.5372596383094788, 'diffusion', 0), ('minimaxir/gpt-2-simple', 0.5367690920829773, 'llm', 0), ('nvidia/apex', 0.5303529500961304, 'ml-dl', 0), ('nielsrogge/transformers-tutorials', 0.5239831805229187, 'study', 1), ('intel/intel-extension-for-pytorch', 0.5219361782073975, 'perf', 1), ('huggingface/transformers', 0.5157749056816101, 'nlp', 2), ('salesforce/blip', 0.5148594379425049, 'diffusion', 0), ('lucidrains/vit-pytorch', 0.5130720138549805, 'ml-dl', 0), ('faster-cpython/tools', 0.5083655118942261, 'perf', 0), ('lucidrains/imagen-pytorch', 0.5046398639678955, 'ml-dl', 0)] | 7 | 4 | null | 0.27 | 83 | 27 | 3 | 0 | 0 | 0 | 0 | 83 | 178 | 90 | 2.1 | 66 |
1,738 | viz | https://github.com/nvidia/tensorrt-llm | ['tensorrt', 'gpu', 'language-model'] | null | [] | [] | null | null | null | nvidia/tensorrt-llm | TensorRT-LLM | 4,276 | 370 | 50 | C++ | https://nvidia.github.io/TensorRT-LLM | TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines. | nvidia | 2024-01-14 | 2023-08-16 | 23 | 179.233533 | https://avatars.githubusercontent.com/u/1728152?v=4 | TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines. | [] | ['gpu', 'language-model', 'tensorrt'] | 2024-01-09 | [('sjtu-ipads/powerinfer', 0.6346943974494934, 'llm', 0), ('exaloop/codon', 0.6340402364730835, 'perf', 0), ('pytorch/pytorch', 0.61689293384552, 'ml-dl', 1), ('ggerganov/ggml', 0.6161227822303772, 'ml', 0), ('google/tf-quant-finance', 0.6080841422080994, 'finance', 1), ('bobazooba/xllm', 0.5863513350486755, 'llm', 0), ('google/gin-config', 0.5778404474258423, 'util', 0), ('rafiqhasan/auto-tensorflow', 0.5734004378318787, 'ml-dl', 0), ('arogozhnikov/einops', 0.5731545686721802, 'ml-dl', 0), ('numba/numba', 0.5688282251358032, 'perf', 0), ('vllm-project/vllm', 0.5639804601669312, 'llm', 0), ('cupy/cupy', 0.5631754994392395, 'math', 1), ('tensorly/tensorly', 0.5586928129196167, 'ml-dl', 0), ('tigerlab-ai/tiger', 0.5560727119445801, 'llm', 0), ('nvidia/warp', 0.5474246740341187, 'sim', 1), ('facebookincubator/aitemplate', 0.5429112315177917, 'ml-dl', 0), ('eleutherai/gpt-neo', 0.5397517681121826, 'llm', 1), ('plasma-umass/scalene', 0.53840172290802, 'profiling', 1), ('next-gpt/next-gpt', 0.5343412160873413, 'llm', 0), ('huggingface/accelerate', 0.5342060923576355, 'ml', 0), ('citadel-ai/langcheck', 0.5307314395904541, 'llm', 1), ('microsoft/torchscale', 0.5302456617355347, 'llm', 0), ('guardrails-ai/guardrails', 0.5297648906707764, 'llm', 0), ('alphasecio/langchain-examples', 0.5265845060348511, 'llm', 0), ('microsoft/autogen', 0.525221586227417, 'llm', 0), ('eth-sri/lmql', 0.524734616279602, 'llm', 1), ('blackhc/toma', 0.5219219923019409, 'ml-dl', 1), ('xl0/lovely-tensors', 0.5217703580856323, 'ml-dl', 0), ('hiyouga/llama-factory', 0.5198065042495728, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.519806444644928, 'llm', 1), ('tensorflow/addons', 0.5190548300743103, 'ml', 0), ('nomic-ai/gpt4all', 0.5173569321632385, 'llm', 1), ('optimalscale/lmflow', 0.5172522068023682, 'llm', 1), ('minimaxir/gpt-2-simple', 0.5171143412590027, 'llm', 0), ('hannibal046/awesome-llm', 0.5133680105209351, 'study', 1), ('microsoft/jarvis', 0.5096875429153442, 'llm', 0), ('pypy/pypy', 0.5079455375671387, 'util', 0), ('juncongmoo/pyllama', 0.5075156092643738, 'llm', 0), ('intel/intel-extension-for-pytorch', 0.505849301815033, 'perf', 0), ('pytorchlightning/pytorch-lightning', 0.5039601922035217, 'ml-dl', 0), ('eleutherai/gpt-neox', 0.5021648406982422, 'llm', 1)] | 4 | 1 | null | 0.83 | 857 | 578 | 5 | 0 | 3 | 12 | 3 | 858 | 2,931 | 90 | 3.4 | 66 |
788 | web | https://github.com/starlite-api/starlite | [] | null | [] | [] | null | null | null | starlite-api/starlite | litestar | 3,806 | 298 | 33 | Python | https://litestar.dev/ | Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs | starlite-api | 2024-01-14 | 2021-12-06 | 112 | 33.938854 | https://avatars.githubusercontent.com/u/97250344?v=4 | Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs | ['api', 'asgi', 'asyncio', 'litestar', 'litestar-api', 'litestar-framework', 'msgspec', 'openapi', 'pydantic', 'rapidoc', 'redoc', 'rest', 'starlite', 'starlite-api', 'swagger'] | ['api', 'asgi', 'asyncio', 'litestar', 'litestar-api', 'litestar-framework', 'msgspec', 'openapi', 'pydantic', 'rapidoc', 'redoc', 'rest', 'starlite', 'starlite-api', 'swagger'] | 2024-01-14 | [('vitalik/django-ninja', 0.7026381492614746, 'web', 3), ('tiangolo/fastapi', 0.6928763389587402, 'web', 7), ('huge-success/sanic', 0.6891716122627258, 'web', 2), ('falconry/falcon', 0.6774393916130066, 'web', 3), ('neoteroi/blacksheep', 0.6740537881851196, 'web', 2), ('python-restx/flask-restx', 0.6593479514122009, 'web', 3), ('pallets/quart', 0.6257473230361938, 'web', 2), ('encode/uvicorn', 0.6137245893478394, 'web', 2), ('asacristani/fastapi-rocket-boilerplate', 0.5981463193893433, 'template', 0), ('jordaneremieff/mangum', 0.5975977182388306, 'web', 2), ('tiangolo/full-stack-fastapi-postgresql', 0.5915384292602539, 'template', 2), ('hugapi/hug', 0.573395848274231, 'util', 0), ('timofurrer/awesome-asyncio', 0.5622597932815552, 'study', 1), ('alirn76/panther', 0.5622544288635254, 'web', 0), ('encode/starlette', 0.5545772314071655, 'web', 0), ('aminalaee/sqladmin', 0.5524939894676208, 'data', 2), ('awtkns/fastapi-crudrouter', 0.550251841545105, 'web', 5), ('s3rius/fastapi-template', 0.5500728487968445, 'web', 1), ('klen/muffin', 0.548690915107727, 'web', 2), ('fastai/ghapi', 0.5345987677574158, 'util', 1), ('rawheel/fastapi-boilerplate', 0.533804178237915, 'web', 1), ('pallets/flask', 0.528308629989624, 'web', 0), ('simonw/datasette', 0.526665985584259, 'data', 1), ('aeternalis-ingenium/fastapi-backend-template', 0.5256733298301697, 'web', 0), ('flet-dev/flet', 0.5249883532524109, 'web', 0), ('shishirpatil/gorilla', 0.5183838605880737, 'llm', 1), ('fastai/fastcore', 0.5158090591430664, 'util', 0), ('emmett-framework/emmett', 0.5148096084594727, 'web', 2), ('pylons/pyramid', 0.5109481811523438, 'web', 0), ('encode/httpx', 0.5098319053649902, 'web', 1), ('sumerc/yappi', 0.5070291757583618, 'profiling', 2), ('pallets/werkzeug', 0.5068367123603821, 'web', 0), ('janetech-inc/fast-api-admin-template', 0.504593551158905, 'template', 0), ('prefecthq/server', 0.5044628381729126, 'util', 0), ('lucidrains/toolformer-pytorch', 0.5022919774055481, 'llm', 0), ('fastapi-users/fastapi-users', 0.5006967186927795, 'web', 1)] | 170 | 4 | null | 21.63 | 572 | 455 | 26 | 0 | 47 | 80 | 47 | 572 | 1,394 | 90 | 2.4 | 66 |
1,847 | data | https://github.com/run-llama/llama-hub | ['data-loader', 'llm'] | null | [] | [] | null | null | null | run-llama/llama-hub | llama-hub | 2,978 | 649 | 43 | Jupyter Notebook | https://llamahub.ai/ | A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain | run-llama | 2024-01-14 | 2023-02-01 | 51 | 57.426997 | https://avatars.githubusercontent.com/u/130722866?v=4 | A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain | [] | ['data-loader', 'llm'] | 2024-01-13 | [('jerryjliu/llama_index', 0.6595434546470642, 'llm', 1), ('zilliztech/gptcache', 0.5969860553741455, 'llm', 1), ('eugeneyan/open-llms', 0.586604654788971, 'study', 1), ('run-llama/llama-lab', 0.5685200095176697, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5623946189880371, 'perf', 0), ('alpha-vllm/llama2-accessory', 0.561208963394165, 'llm', 0), ('ajndkr/lanarky', 0.5594974160194397, 'llm', 0), ('ray-project/llm-applications', 0.5521401166915894, 'llm', 0), ('lightning-ai/lit-gpt', 0.5486422181129456, 'llm', 0), ('berriai/litellm', 0.5469061136245728, 'llm', 1), ('salesforce/xgen', 0.542940616607666, 'llm', 1), ('bentoml/openllm', 0.5397924184799194, 'ml-ops', 1), ('predibase/lorax', 0.5340386629104614, 'llm', 1), ('pathwaycom/llm-app', 0.5336598753929138, 'llm', 1), ('tloen/alpaca-lora', 0.5322900414466858, 'llm', 0), ('microsoft/llama-2-onnx', 0.5180464386940002, 'llm', 0), ('jzhang38/tinyllama', 0.5164508819580078, 'llm', 0), ('shishirpatil/gorilla', 0.5163030028343201, 'llm', 1), ('bigscience-workshop/petals', 0.5156326293945312, 'data', 0), ('alphasecio/langchain-examples', 0.5134257674217224, 'llm', 1), ('mshumer/gpt-llm-trainer', 0.5054514408111572, 'llm', 0), ('deepset-ai/haystack', 0.5051847100257874, 'llm', 0), ('nomic-ai/gpt4all', 0.5034949779510498, 'llm', 0), ('lancedb/lancedb', 0.5028201937675476, 'data', 0)] | 224 | 4 | null | 14.58 | 286 | 240 | 12 | 0 | 0 | 59 | 59 | 285 | 330 | 90 | 1.2 | 66 |
1,188 | diffusion | https://github.com/stability-ai/stablediffusion | ['diffusion', 'image-generation'] | null | [] | [] | null | null | null | stability-ai/stablediffusion | stablediffusion | 33,628 | 4,452 | 417 | Python | null | High-Resolution Image Synthesis with Latent Diffusion Models | stability-ai | 2024-01-14 | 2022-11-23 | 61 | 543.639723 | https://avatars.githubusercontent.com/u/100950301?v=4 | High-Resolution Image Synthesis with Latent Diffusion Models | [] | ['diffusion', 'image-generation'] | 2023-03-25 | [('compvis/latent-diffusion', 1.0000004768371582, 'diffusion', 2), ('albarji/mixture-of-diffusers', 0.690674364566803, 'diffusion', 0), ('compvis/stable-diffusion', 0.6550443768501282, 'diffusion', 2), ('openai/glide-text2im', 0.6436024308204651, 'diffusion', 0), ('huggingface/diffusers', 0.6299402713775635, 'diffusion', 2), ('sharonzhou/long_stable_diffusion', 0.5753588676452637, 'diffusion', 0), ('openai/point-e', 0.5376940965652466, 'util', 0), ('timothybrooks/instruct-pix2pix', 0.5207132697105408, 'diffusion', 0), ('kakaobrain/rq-vae-transformer', 0.5072489380836487, 'ml-dl', 0)] | 18 | 4 | null | 0.58 | 34 | 7 | 14 | 10 | 0 | 0 | 0 | 34 | 34 | 90 | 1 | 65 |
756 | ml-dl | https://github.com/xinntao/real-esrgan | [] | null | [] | [] | null | null | null | xinntao/real-esrgan | Real-ESRGAN | 24,620 | 3,149 | 216 | Python | null | Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration. | xinntao | 2024-01-14 | 2021-07-19 | 132 | 186.313514 | null | Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration. | ['amine', 'denoise', 'esrgan', 'image-restoration', 'jpeg-compression', 'pytorch', 'real-esrgan', 'super-resolution'] | ['amine', 'denoise', 'esrgan', 'image-restoration', 'jpeg-compression', 'pytorch', 'real-esrgan', 'super-resolution'] | 2022-09-20 | [('xpixelgroup/basicsr', 0.6734346151351929, 'ml-dl', 3), ('tencentarc/gfpgan', 0.5772732496261597, 'ml', 3)] | 11 | 7 | null | 0 | 66 | 14 | 30 | 16 | 0 | 8 | 8 | 66 | 85 | 90 | 1.3 | 65 |
827 | util | https://github.com/micropython/micropython | [] | null | [] | [] | null | null | null | micropython/micropython | micropython | 17,769 | 7,083 | 735 | C | https://micropython.org | MicroPython - a lean and efficient Python implementation for microcontrollers and constrained systems | micropython | 2024-01-14 | 2013-12-20 | 527 | 33.680747 | https://avatars.githubusercontent.com/u/6298560?v=4 | MicroPython - a lean and efficient Python implementation for microcontrollers and constrained systems | ['embedded', 'microcontroller', 'micropython'] | ['embedded', 'microcontroller', 'micropython'] | 2024-01-10 | [('adafruit/circuitpython', 0.7091054916381836, 'util', 3), ('pypy/pypy', 0.6625933051109314, 'util', 0), ('pyston/pyston', 0.6496843695640564, 'util', 0), ('plasma-umass/scalene', 0.6017813086509705, 'profiling', 0), ('exaloop/codon', 0.5922623872756958, 'perf', 0), ('cython/cython', 0.5850077271461487, 'util', 0), ('ipython/ipyparallel', 0.5837920904159546, 'perf', 0), ('willmcgugan/textual', 0.5815902352333069, 'term', 0), ('google/gin-config', 0.578527569770813, 'util', 0), ('fastai/fastcore', 0.5780920386314392, 'util', 0), ('google/jax', 0.5700966119766235, 'ml', 0), ('python/cpython', 0.5564913153648376, 'util', 0), ('pallets/quart', 0.5557764768600464, 'web', 0), ('ethereum/py-evm', 0.5545228719711304, 'crypto', 0), ('intel/intel-extension-for-pytorch', 0.5541401505470276, 'perf', 0), ('pympler/pympler', 0.5511940121650696, 'perf', 0), ('artemyk/dynpy', 0.5470327734947205, 'sim', 0), ('dddomodossola/remi', 0.5408753752708435, 'gui', 0), ('hoffstadt/dearpygui', 0.5389625430107117, 'gui', 0), ('agronholm/apscheduler', 0.5366904139518738, 'util', 0), ('kubeflow/fairing', 0.5345472693443298, 'ml-ops', 0), ('joblib/joblib', 0.5310302376747131, 'util', 0), ('pyinfra-dev/pyinfra', 0.5298929214477539, 'util', 0), ('numpy/numpy', 0.5278494358062744, 'math', 0), ('numba/numba', 0.5256375670433044, 'perf', 0), ('python-trio/trio', 0.5247344970703125, 'perf', 0), ('wxwidgets/phoenix', 0.5213609933853149, 'gui', 0), ('pytoolz/toolz', 0.5203608870506287, 'util', 0), ('aws/chalice', 0.5198830366134644, 'web', 0), ('pallets/flask', 0.5177249908447266, 'web', 0), ('eleutherai/pyfra', 0.5175337195396423, 'ml', 0), ('py4j/py4j', 0.5158247947692871, 'util', 0), ('pythonspeed/filprofiler', 0.5140711069107056, 'profiling', 0), ('pytables/pytables', 0.5130558013916016, 'data', 0), ('nvidia/warp', 0.512362003326416, 'sim', 0), ('pytorch/pytorch', 0.5111660361289978, 'ml-dl', 0), ('erotemic/ubelt', 0.5087762475013733, 'util', 0), ('allrod5/injectable', 0.5082573294639587, 'util', 0), ('falconry/falcon', 0.507040798664093, 'web', 0), ('beeware/toga', 0.5063884258270264, 'gui', 0), ('alexmojaki/snoop', 0.505521297454834, 'debug', 0), ('1200wd/bitcoinlib', 0.5035257935523987, 'crypto', 0), ('numba/llvmlite', 0.5028732419013977, 'util', 0)] | 613 | 3 | null | 19.92 | 536 | 284 | 123 | 5 | 4 | 6 | 4 | 537 | 1,681 | 90 | 3.1 | 65 |
30 | web | https://github.com/huge-success/sanic | [] | null | [] | [] | null | null | null | huge-success/sanic | sanic | 17,531 | 1,545 | 408 | Python | https://sanic.dev | Accelerate your web app development | Build fast. Run fast. | huge-success | 2024-01-13 | 2016-05-26 | 400 | 43.749376 | https://avatars.githubusercontent.com/u/25215992?v=4 | Accelerate your web app development | Build fast. Run fast. | ['api-server', 'asgi', 'asyncio', 'framework', 'sanic', 'web', 'web-framework', 'web-server'] | ['api-server', 'asgi', 'asyncio', 'framework', 'sanic', 'web', 'web-framework', 'web-server'] | 2024-01-01 | [('neoteroi/blacksheep', 0.7380421161651611, 'web', 4), ('pallets/quart', 0.7020831108093262, 'web', 2), ('starlite-api/starlite', 0.6891716122627258, 'web', 2), ('encode/uvicorn', 0.633416473865509, 'web', 2), ('tiangolo/fastapi', 0.6080839037895203, 'web', 3), ('alirn76/panther', 0.6031531095504761, 'web', 1), ('encode/starlette', 0.5865360498428345, 'web', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5729467868804932, 'template', 0), ('klen/muffin', 0.5701971054077148, 'web', 2), ('pallets/flask', 0.5633546710014343, 'web', 1), ('tiangolo/asyncer', 0.5628356337547302, 'perf', 1), ('vitalik/django-ninja', 0.5478051900863647, 'web', 0), ('emmett-framework/emmett', 0.5460001230239868, 'web', 3), ('aio-libs/aiohttp', 0.5445988774299622, 'web', 1), ('reflex-dev/reflex', 0.5383414030075073, 'web', 1), ('falconry/falcon', 0.5344210267066956, 'web', 3), ('flet-dev/flet', 0.5318177342414856, 'web', 1), ('encode/httpx', 0.5279699563980103, 'web', 1), ('python-restx/flask-restx', 0.5204745531082153, 'web', 0), ('jordaneremieff/mangum', 0.511349081993103, 'web', 3), ('magicstack/uvloop', 0.5082210898399353, 'util', 1)] | 340 | 6 | null | 2.02 | 93 | 57 | 93 | 0 | 4 | 11 | 4 | 93 | 149 | 90 | 1.6 | 65 |