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1,289 | llm | https://github.com/blinkdl/chatrwkv | [] | null | [] | [] | null | null | null | blinkdl/chatrwkv | ChatRWKV | 9,013 | 670 | 90 | Python | null | ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source. | blinkdl | 2024-01-14 | 2023-01-13 | 54 | 165.159686 | null | ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source. | ['chatbot', 'chatgpt', 'language-model', 'pytorch', 'rnn', 'rwkv'] | ['chatbot', 'chatgpt', 'language-model', 'pytorch', 'rnn', 'rwkv'] | 2023-12-27 | [('xtekky/gpt4free', 0.6857205033302307, 'llm', 3), ('run-llama/rags', 0.678069531917572, 'llm', 2), ('blinkdl/rwkv-lm', 0.6400032043457031, 'llm', 5), ('embedchain/embedchain', 0.6271498203277588, 'llm', 1), ('nomic-ai/gpt4all', 0.6257155537605286, 'llm', 2), ('lm-sys/fastchat', 0.6127018928527832, 'llm', 2), ('togethercomputer/openchatkit', 0.6018038392066956, 'nlp', 1), ('killianlucas/open-interpreter', 0.6001401543617249, 'llm', 1), ('microsoft/autogen', 0.5980231761932373, 'llm', 2), ('fasteval/fasteval', 0.5970721244812012, 'llm', 0), ('minimaxir/simpleaichat', 0.5946717262268066, 'llm', 1), ('databrickslabs/dolly', 0.592911422252655, 'llm', 1), ('next-gpt/next-gpt', 0.5798339247703552, 'llm', 1), ('openlmlab/moss', 0.5662409067153931, 'llm', 2), ('openai/tiktoken', 0.5641686320304871, 'nlp', 1), ('rasahq/rasa', 0.5604526400566101, 'llm', 1), ('deeppavlov/deeppavlov', 0.5481441617012024, 'nlp', 1), ('mlc-ai/web-llm', 0.5393033623695374, 'llm', 2), ('openai/openai-cookbook', 0.5351440906524658, 'ml', 1), ('allenai/allennlp', 0.5303969979286194, 'nlp', 1), ('gunthercox/chatterbot', 0.5218847393989563, 'nlp', 1), ('langchain-ai/chat-langchain', 0.521385908126831, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5196929574012756, 'nlp', 0), ('nvidia/nemo', 0.5173482894897461, 'nlp', 1), ('mayooear/gpt4-pdf-chatbot-langchain', 0.5159780979156494, 'llm', 0), ('laion-ai/open-assistant', 0.5142605900764465, 'llm', 2), ('chatarena/chatarena', 0.5140795111656189, 'llm', 1), ('rcgai/simplyretrieve', 0.5114522576332092, 'llm', 0), ('speechbrain/speechbrain', 0.5112695693969727, 'nlp', 2), ('thudm/chatglm2-6b', 0.5033798813819885, 'llm', 0)] | 17 | 4 | null | 5.88 | 14 | 7 | 12 | 1 | 0 | 0 | 0 | 14 | 7 | 90 | 0.5 | 61 |
1,074 | nlp | https://github.com/togethercomputer/openchatkit | ['chatbot'] | OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots | [] | [] | null | null | null | togethercomputer/openchatkit | OpenChatKit | 8,958 | 1,024 | 123 | Python | null | null | togethercomputer | 2024-01-14 | 2023-03-03 | 47 | 188.306306 | https://avatars.githubusercontent.com/u/109101822?v=4 | OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots | [] | ['chatbot'] | 2023-08-17 | [('embedchain/embedchain', 0.7426310181617737, 'llm', 0), ('gunthercox/chatterbot', 0.6964467167854309, 'nlp', 1), ('rasahq/rasa', 0.6932374835014343, 'llm', 1), ('nomic-ai/gpt4all', 0.6839218139648438, 'llm', 1), ('minimaxir/simpleaichat', 0.6666284203529358, 'llm', 0), ('deeppavlov/deeppavlov', 0.6648150086402893, 'nlp', 1), ('run-llama/rags', 0.6478996872901917, 'llm', 1), ('rcgai/simplyretrieve', 0.6417977213859558, 'llm', 0), ('larsbaunwall/bricky', 0.6274131536483765, 'llm', 0), ('laion-ai/open-assistant', 0.6049430966377258, 'llm', 0), ('blinkdl/chatrwkv', 0.6018038392066956, 'llm', 1), ('langchain-ai/chat-langchain', 0.6002198457717896, 'llm', 0), ('krohling/bondai', 0.596705973148346, 'llm', 0), ('lm-sys/fastchat', 0.5938577651977539, 'llm', 1), ('cheshire-cat-ai/core', 0.5846368074417114, 'llm', 1), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5749940872192383, 'llm', 0), ('killianlucas/open-interpreter', 0.570201575756073, 'llm', 0), ('prefecthq/marvin', 0.5622385144233704, 'nlp', 0), ('xtekky/gpt4free', 0.5519025325775146, 'llm', 1), ('kalliope-project/kalliope', 0.5493156909942627, 'util', 0), ('mayooear/gpt4-pdf-chatbot-langchain', 0.5483038425445557, 'llm', 0), ('deepset-ai/haystack', 0.5454091429710388, 'llm', 0), ('deep-diver/llm-as-chatbot', 0.5419533848762512, 'llm', 1), ('nvidia/nemo', 0.5391964912414551, 'nlp', 0), ('errbotio/errbot', 0.5380634665489197, 'nlp', 1), ('openlmlab/moss', 0.5363262295722961, 'llm', 0), ('openai/gpt-discord-bot', 0.5345660448074341, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5263169407844543, 'nlp', 0), ('weaviate/verba', 0.5258392691612244, 'llm', 0), ('fasteval/fasteval', 0.519807755947113, 'llm', 0), ('hwchase17/langchain', 0.5152731537818909, 'llm', 1), ('openai/openai-cookbook', 0.51520174741745, 'ml', 0), ('pathwaycom/llm-app', 0.5052575469017029, 'llm', 1), ('eternnoir/pytelegrambotapi', 0.5013675093650818, 'util', 0)] | 19 | 6 | null | 2.15 | 8 | 2 | 11 | 5 | 0 | 2 | 2 | 8 | 4 | 90 | 0.5 | 61 |
1,361 | llm | https://github.com/artidoro/qlora | ['language-model'] | null | [] | [] | null | null | null | artidoro/qlora | qlora | 8,702 | 762 | 81 | Jupyter Notebook | https://arxiv.org/abs/2305.14314 | QLoRA: Efficient Finetuning of Quantized LLMs | artidoro | 2024-01-14 | 2023-05-11 | 37 | 230.734848 | null | QLoRA: Efficient Finetuning of Quantized LLMs | [] | ['language-model'] | 2023-07-24 | [('opengvlab/omniquant', 0.7345274090766907, 'llm', 0), ('squeezeailab/squeezellm', 0.6456478834152222, 'llm', 0), ('hiyouga/llama-factory', 0.6366949081420898, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.6366947889328003, 'llm', 1), ('bobazooba/xllm', 0.6219983100891113, 'llm', 0), ('timdettmers/bitsandbytes', 0.6154015064239502, 'util', 0), ('ray-project/ray-llm', 0.6143306493759155, 'llm', 0), ('salesforce/xgen', 0.6102448105812073, 'llm', 1), ('juncongmoo/pyllama', 0.5865978002548218, 'llm', 0), ('vllm-project/vllm', 0.5857405066490173, 'llm', 0), ('young-geng/easylm', 0.574920654296875, 'llm', 1), ('sjtu-ipads/powerinfer', 0.5710045695304871, 'llm', 0), ('amazon-science/dq-bart', 0.5504317283630371, 'nlp', 0), ('predibase/llm_distillation_playbook', 0.5419549345970154, 'llm', 0), ('cg123/mergekit', 0.5330007076263428, 'llm', 0), ('vahe1994/spqr', 0.5260251760482788, 'llm', 0), ('lightning-ai/lit-gpt', 0.5197663903236389, 'llm', 0), ('hao-ai-lab/lookaheaddecoding', 0.5174603462219238, 'llm', 0), ('huawei-noah/pretrained-language-model', 0.5163824558258057, 'nlp', 0), ('microsoft/torchscale', 0.5133755207061768, 'llm', 0), ('lightning-ai/lit-llama', 0.5125903487205505, 'llm', 1), ('lianjiatech/belle', 0.5086693167686462, 'llm', 0), ('li-plus/chatglm.cpp', 0.5086432099342346, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5075502395629883, 'perf', 0), ('mooler0410/llmspracticalguide', 0.5064951181411743, 'study', 0), ('eugeneyan/open-llms', 0.5061990022659302, 'study', 0), ('ibm/dromedary', 0.5037577748298645, 'llm', 1), ('thudm/chatglm2-6b', 0.5035903453826904, 'llm', 0), ('optimalscale/lmflow', 0.5009582042694092, 'llm', 1)] | 16 | 4 | null | 1.37 | 34 | 12 | 8 | 6 | 0 | 0 | 0 | 33 | 31 | 90 | 0.9 | 61 |
609 | testing | https://github.com/robotframework/robotframework | [] | null | [] | [] | null | null | null | robotframework/robotframework | robotframework | 8,634 | 2,217 | 475 | Python | http://robotframework.org | Generic automation framework for acceptance testing and RPA | robotframework | 2024-01-13 | 2014-06-27 | 500 | 17.248288 | https://avatars.githubusercontent.com/u/574284?v=4 | Generic automation framework for acceptance testing and RPA | ['attd', 'automation', 'bdd', 'robotframework', 'rpa', 'testautomation', 'testing'] | ['attd', 'automation', 'bdd', 'robotframework', 'rpa', 'testautomation', 'testing'] | 2024-01-11 | [('vedro-universe/vedro', 0.5252175331115723, 'testing', 1), ('seleniumbase/seleniumbase', 0.5185773968696594, 'testing', 0)] | 193 | 4 | null | 13.5 | 280 | 216 | 116 | 0 | 12 | 15 | 12 | 280 | 408 | 90 | 1.5 | 61 |
312 | util | https://github.com/pypa/pipx | [] | null | [] | [] | null | null | null | pypa/pipx | pipx | 7,789 | 361 | 75 | Python | https://pipx.pypa.io | Install and Run Python Applications in Isolated Environments | pypa | 2024-01-14 | 2018-10-06 | 277 | 28.075695 | https://avatars.githubusercontent.com/u/647025?v=4 | Install and Run Python Applications in Isolated Environments | ['cli', 'pip', 'venv'] | ['cli', 'pip', 'venv'] | 2024-01-13 | [('pyenv/pyenv', 0.6269603371620178, 'util', 2), ('pypa/virtualenv', 0.6216922998428345, 'util', 2), ('pypa/pipenv', 0.6215226650238037, 'util', 2), ('ofek/pyapp', 0.604620099067688, 'util', 1), ('beeware/briefcase', 0.5395711064338684, 'util', 0), ('pantsbuild/pex', 0.5113623738288879, 'util', 1), ('pomponchik/instld', 0.5103548765182495, 'util', 2), ('pypa/hatch', 0.5080375671386719, 'util', 1), ('pyinstaller/pyinstaller', 0.5007230639457703, 'util', 0)] | 124 | 4 | null | 2.52 | 264 | 199 | 64 | 0 | 9 | 12 | 9 | 264 | 474 | 90 | 1.8 | 61 |
1,047 | ml-dl | https://github.com/lucidrains/imagen-pytorch | [] | null | [] | [] | null | null | null | lucidrains/imagen-pytorch | imagen-pytorch | 7,563 | 714 | 111 | Python | null | Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch | lucidrains | 2024-01-13 | 2022-05-23 | 88 | 85.80389 | null | Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch | ['artificial-intelligence', 'deep-learning', 'imagination-machine', 'text-to-image', 'text-to-video'] | ['artificial-intelligence', 'deep-learning', 'imagination-machine', 'text-to-image', 'text-to-video'] | 2024-01-12 | [('lucidrains/dalle2-pytorch', 0.7950653433799744, 'diffusion', 3), ('hysts/pytorch_image_classification', 0.6431624889373779, 'ml-dl', 0), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.6227165460586548, 'web', 1), ('pytorch/ignite', 0.6169648766517639, 'ml-dl', 1), ('nvlabs/gcvit', 0.6131131052970886, 'diffusion', 1), ('saharmor/dalle-playground', 0.5938807725906372, 'diffusion', 2), ('skorch-dev/skorch', 0.5915490388870239, 'ml-dl', 0), ('alibaba/easynlp', 0.5900583267211914, 'nlp', 1), ('lucidrains/deep-daze', 0.588476300239563, 'ml', 3), ('salesforce/blip', 0.579346776008606, 'diffusion', 0), ('open-mmlab/mmediting', 0.5784053206443787, 'ml', 1), ('minimaxir/textgenrnn', 0.5763087272644043, 'nlp', 1), ('lucidrains/vit-pytorch', 0.5685757994651794, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5683515667915344, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.5663982033729553, 'perf', 1), ('pyg-team/pytorch_geometric', 0.5598738193511963, 'ml-dl', 1), ('mrdbourke/pytorch-deep-learning', 0.5554819703102112, 'study', 1), ('allenai/allennlp', 0.5545222163200378, 'nlp', 1), ('rwightman/pytorch-image-models', 0.5502446889877319, 'ml-dl', 0), ('activeloopai/deeplake', 0.5490372776985168, 'ml-ops', 1), ('karpathy/micrograd', 0.5438899993896484, 'study', 0), ('automatic1111/stable-diffusion-webui', 0.5401318073272705, 'diffusion', 1), ('lightly-ai/lightly', 0.5377395153045654, 'ml', 1), ('openai/clip', 0.5373484492301941, 'ml-dl', 1), ('jina-ai/clip-as-service', 0.5368449091911316, 'nlp', 1), ('huggingface/diffusers', 0.5299099087715149, 'diffusion', 1), ('huggingface/transformers', 0.5293651223182678, 'nlp', 1), ('ddbourgin/numpy-ml', 0.5289348363876343, 'ml', 0), ('nomic-ai/nomic', 0.5279374718666077, 'nlp', 0), ('nicolas-chaulet/torch-points3d', 0.5233572125434875, 'ml', 0), ('deci-ai/super-gradients', 0.5232393145561218, 'ml-dl', 1), ('lutzroeder/netron', 0.52129065990448, 'ml', 1), ('kornia/kornia', 0.5201680064201355, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.5199929475784302, 'study', 1), ('microsoft/onnxruntime', 0.519209623336792, 'ml', 1), ('denys88/rl_games', 0.5174486041069031, 'ml-rl', 1), ('jaidedai/easyocr', 0.5161765217781067, 'data', 1), ('davidadsp/generative_deep_learning_2nd_edition', 0.5147601962089539, 'study', 1), ('nvidia/deeplearningexamples', 0.5135546326637268, 'ml-dl', 1), ('sharonzhou/long_stable_diffusion', 0.5128797292709351, 'diffusion', 0), ('neuralmagic/sparseml', 0.512857973575592, 'ml-dl', 0), ('tensorlayer/tensorlayer', 0.5119508504867554, 'ml-rl', 2), ('awslabs/autogluon', 0.5101648569107056, 'ml', 1), ('deepmind/deepmind-research', 0.5075194835662842, 'ml', 0), ('huggingface/datasets', 0.5067300200462341, 'nlp', 1), ('pytorch-labs/gpt-fast', 0.5046398639678955, 'llm', 0), ('fepegar/torchio', 0.5043638348579407, 'ml-dl', 1), ('xl0/lovely-tensors', 0.5031198263168335, 'ml-dl', 1), ('nvlabs/prismer', 0.5019423961639404, 'diffusion', 0)] | 20 | 3 | null | 1 | 13 | 3 | 20 | 0 | 40 | 212 | 40 | 13 | 16 | 90 | 1.2 | 61 |
344 | jupyter | https://github.com/mwouts/jupytext | [] | null | [] | [] | null | null | null | mwouts/jupytext | jupytext | 6,301 | 387 | 69 | Python | https://jupytext.readthedocs.io | Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts | mwouts | 2024-01-14 | 2018-06-15 | 293 | 21.46326 | null | Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts | ['hydrogen', 'jupyter-notebook', 'jupyterlab', 'jupyterlab-extension', 'knitr', 'markdown', 'notebooks', 'rmarkdown', 'rstudio', 'version-control'] | ['hydrogen', 'jupyter-notebook', 'jupyterlab', 'jupyterlab-extension', 'knitr', 'markdown', 'notebooks', 'rmarkdown', 'rstudio', 'version-control'] | 2024-01-13 | [('jupyter/nbformat', 0.6959807276725769, 'jupyter', 0), ('jupyter/notebook', 0.6791135668754578, 'jupyter', 1), ('voila-dashboards/voila', 0.6650576591491699, 'jupyter', 2), ('jupyter-widgets/ipywidgets', 0.6579967737197876, 'jupyter', 1), ('jupyterlab/jupyterlab-desktop', 0.6525211930274963, 'jupyter', 2), ('jupyter-lsp/jupyterlab-lsp', 0.6457168459892273, 'jupyter', 3), ('aws/graph-notebook', 0.6454940438270569, 'jupyter', 1), ('jupyter/nbdime', 0.6408078074455261, 'jupyter', 3), ('cohere-ai/notebooks', 0.6391822695732117, 'llm', 1), ('nteract/papermill', 0.632023811340332, 'jupyter', 1), ('jupyter/nbconvert', 0.6044052839279175, 'jupyter', 0), ('vizzuhq/ipyvizzu', 0.5986511707305908, 'jupyter', 1), ('jupyterlab/jupyterlab', 0.5835863947868347, 'jupyter', 1), ('jupyter/nbgrader', 0.5783310532569885, 'jupyter', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5749877095222473, 'study', 0), ('nbqa-dev/nbqa', 0.5719586610794067, 'jupyter', 1), ('quantopian/qgrid', 0.5685391426086426, 'jupyter', 0), ('ipython/ipykernel', 0.5664380788803101, 'util', 1), ('computationalmodelling/nbval', 0.5556824803352356, 'jupyter', 1), ('jupyterlite/jupyterlite', 0.5492159128189087, 'jupyter', 2), ('python-markdown/markdown', 0.5461102724075317, 'util', 1), ('jakevdp/pythondatasciencehandbook', 0.5404434204101562, 'study', 1), ('mamba-org/gator', 0.5371402502059937, 'jupyter', 2), ('tkrabel/bamboolib', 0.5347379446029663, 'pandas', 2), ('maartenbreddels/ipyvolume', 0.520946741104126, 'jupyter', 1), ('xiaohk/stickyland', 0.5160862803459167, 'jupyter', 2), ('bloomberg/ipydatagrid', 0.5105863809585571, 'jupyter', 1)] | 85 | 6 | null | 3.15 | 95 | 66 | 68 | 0 | 13 | 26 | 13 | 95 | 244 | 90 | 2.6 | 61 |
141 | nlp | https://github.com/neuml/txtai | [] | null | [] | [] | null | null | null | neuml/txtai | txtai | 5,982 | 443 | 77 | Python | https://neuml.github.io/txtai | 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows | neuml | 2024-01-14 | 2020-08-09 | 181 | 32.997636 | https://avatars.githubusercontent.com/u/59890304?v=4 | 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows | ['embeddings', 'information-retrieval', 'language-model', 'large-language-models', 'llm', 'machine-learning', 'neural-search', 'nlp', 'rag', 'retrieval-augmented-generation', 'search', 'search-engine', 'semantic-search', 'sentence-embeddings', 'transformers', 'txtai', 'vector-database', 'vector-search', 'vector-search-engine'] | ['embeddings', 'information-retrieval', 'language-model', 'large-language-models', 'llm', 'machine-learning', 'neural-search', 'nlp', 'rag', 'retrieval-augmented-generation', 'search', 'search-engine', 'semantic-search', 'sentence-embeddings', 'transformers', 'txtai', 'vector-database', 'vector-search', 'vector-search-engine'] | 2024-01-12 | [('paddlepaddle/paddlenlp', 0.7093960642814636, 'llm', 5), ('llmware-ai/llmware', 0.7031641602516174, 'llm', 9), ('chroma-core/chroma', 0.6690793633460999, 'data', 1), ('qdrant/fastembed', 0.6601556539535522, 'ml', 4), ('jina-ai/vectordb', 0.6555339097976685, 'data', 4), ('muennighoff/sgpt', 0.6413739323616028, 'llm', 6), ('deepset-ai/haystack', 0.635899007320404, 'llm', 7), ('intellabs/fastrag', 0.6202690005302429, 'nlp', 5), ('milvus-io/bootcamp', 0.6126426458358765, 'data', 3), ('ddangelov/top2vec', 0.608359694480896, 'nlp', 1), ('nomic-ai/semantic-search-app-template', 0.6002048254013062, 'study', 1), ('jina-ai/clip-as-service', 0.5824137330055237, 'nlp', 1), ('eleutherai/the-pile', 0.5822166800498962, 'data', 1), ('docarray/docarray', 0.5759537816047668, 'data', 3), ('activeloopai/deeplake', 0.575560450553894, 'ml-ops', 5), ('lancedb/lancedb', 0.574266254901886, 'data', 3), ('jina-ai/finetuner', 0.56916743516922, 'ml', 1), ('explosion/spacy-llm', 0.5675748586654663, 'llm', 4), ('qdrant/qdrant', 0.5641199350357056, 'data', 7), ('awslabs/dgl-ke', 0.5560591220855713, 'ml', 1), ('zilliztech/gptcache', 0.5468195080757141, 'llm', 3), ('infinitylogesh/mutate', 0.5397577285766602, 'nlp', 1), ('koaning/embetter', 0.538155198097229, 'data', 0), ('amansrivastava17/embedding-as-service', 0.5340142250061035, 'nlp', 2), ('sebischair/lbl2vec', 0.5315554738044739, 'nlp', 2), ('kagisearch/vectordb', 0.529229998588562, 'data', 2), ('hegelai/prompttools', 0.5288627743721008, 'llm', 4), ('plasticityai/magnitude', 0.526243269443512, 'nlp', 3), ('alibaba/easynlp', 0.5239185690879822, 'nlp', 3), ('ukplab/sentence-transformers', 0.5237442255020142, 'nlp', 3), ('weaviate/semantic-search-through-wikipedia-with-weaviate', 0.5210995674133301, 'data', 1), ('koaning/whatlies', 0.5187655687332153, 'nlp', 2), ('marqo-ai/marqo', 0.5169413089752197, 'ml', 7), ('paddlepaddle/rocketqa', 0.5149143934249878, 'nlp', 2), ('huggingface/transformers', 0.5143444538116455, 'nlp', 3), ('salesforce/xgen', 0.5134238600730896, 'llm', 4), ('lm-sys/fastchat', 0.5114730000495911, 'llm', 1), ('deeppavlov/deeppavlov', 0.5076900720596313, 'nlp', 2), ('mooler0410/llmspracticalguide', 0.5057186484336853, 'study', 2), ('allenai/allennlp', 0.50567227602005, 'nlp', 1), ('dylanhogg/llmgraph', 0.5045521259307861, 'ml', 1), ('microsoft/vert-papers', 0.5036661028862, 'nlp', 1), ('princeton-nlp/alce', 0.5001633763313293, 'llm', 0), ('lianjiatech/belle', 0.5000015497207642, 'llm', 0)] | 12 | 7 | null | 5.67 | 74 | 59 | 42 | 0 | 8 | 10 | 8 | 74 | 152 | 90 | 2.1 | 61 |
82 | util | https://github.com/sphinx-doc/sphinx | [] | null | [] | [] | null | null | null | sphinx-doc/sphinx | sphinx | 5,855 | 2,037 | 148 | Python | https://www.sphinx-doc.org/ | The Sphinx documentation generator | sphinx-doc | 2024-01-14 | 2015-01-02 | 473 | 12.363499 | https://avatars.githubusercontent.com/u/9928167?v=4 | The Sphinx documentation generator | ['docs', 'documentation', 'documentation-tool', 'markdown', 'restructuredtext', 'sphinx'] | ['docs', 'documentation', 'documentation-tool', 'markdown', 'restructuredtext', 'sphinx'] | 2024-01-14 | [('executablebooks/jupyter-book', 0.753897488117218, 'jupyter', 0), ('mitmproxy/pdoc', 0.7031545042991638, 'util', 3), ('pdoc3/pdoc', 0.6652024388313293, 'util', 3), ('squidfunk/mkdocs-material', 0.6544510126113892, 'util', 1), ('mkdocs/mkdocs', 0.6297897100448608, 'util', 2), ('mkdocstrings/mkdocstrings', 0.5597922801971436, 'util', 0), ('getpelican/pelican', 0.5320377349853516, 'web', 0)] | 796 | 7 | null | 14.88 | 299 | 202 | 110 | 0 | 15 | 21 | 15 | 299 | 447 | 90 | 1.5 | 61 |
342 | web | https://github.com/vitalik/django-ninja | [] | null | [] | [] | null | null | null | vitalik/django-ninja | django-ninja | 5,676 | 346 | 75 | Python | https://django-ninja.dev | 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs | vitalik | 2024-01-14 | 2020-05-19 | 193 | 29.409326 | null | 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs | ['django', 'django-ninja', 'openapi', 'pydantic', 'rest-api', 'swagger', 'swagger-ui'] | ['django', 'django-ninja', 'openapi', 'pydantic', 'rest-api', 'swagger', 'swagger-ui'] | 2024-01-08 | [('tiangolo/fastapi', 0.8338611721992493, 'web', 4), ('python-restx/flask-restx', 0.7110880613327026, 'web', 1), ('starlite-api/starlite', 0.7026381492614746, 'web', 3), ('awtkns/fastapi-crudrouter', 0.6941371560096741, 'web', 2), ('hugapi/hug', 0.6697272658348083, 'util', 0), ('asacristani/fastapi-rocket-boilerplate', 0.6605289578437805, 'template', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.6353817582130432, 'template', 2), ('willmcgugan/textual', 0.6247105002403259, 'term', 0), ('falconry/falcon', 0.6103278994560242, 'web', 0), ('rawheel/fastapi-boilerplate', 0.6011227369308472, 'web', 1), ('shishirpatil/gorilla', 0.5843652486801147, 'llm', 0), ('fastai/ghapi', 0.58127361536026, 'util', 1), ('mitmproxy/pdoc', 0.5793086886405945, 'util', 0), ('s3rius/fastapi-template', 0.5742310285568237, 'web', 0), ('fastai/fastcore', 0.5651664137840271, 'util', 0), ('pyeve/eve', 0.563342809677124, 'web', 0), ('alirn76/panther', 0.5587133169174194, 'web', 0), ('openai/openai-python', 0.5567331910133362, 'util', 0), ('kivy/kivy', 0.5482510328292847, 'util', 0), ('huge-success/sanic', 0.5478051900863647, 'web', 0), ('pallets/flask', 0.5399484038352966, 'web', 0), ('prefecthq/server', 0.5366072654724121, 'util', 0), ('plotly/dash', 0.5318993926048279, 'viz', 0), ('lucidrains/toolformer-pytorch', 0.528582751750946, 'llm', 0), ('fastapi-admin/fastapi-admin', 0.5257643461227417, 'web', 0), ('bottlepy/bottle', 0.5206802487373352, 'web', 0), ('flet-dev/flet', 0.5206228494644165, 'web', 0), ('ml-tooling/opyrator', 0.5184093713760376, 'viz', 1), ('langchain-ai/opengpts', 0.5144355297088623, 'llm', 0), ('reflex-dev/reflex', 0.512046754360199, 'web', 0), ('simple-salesforce/simple-salesforce', 0.508848249912262, 'data', 0), ('oobabooga/text-generation-webui', 0.5028524398803711, 'llm', 0), ('alphasecio/langchain-examples', 0.5026804804801941, 'llm', 0), ('eternnoir/pytelegrambotapi', 0.5017293095588684, 'util', 0)] | 125 | 3 | null | 4.52 | 208 | 110 | 44 | 0 | 13 | 11 | 13 | 208 | 362 | 90 | 1.7 | 61 |
754 | sim | https://github.com/qiskit/qiskit | [] | null | [] | [] | null | null | null | qiskit/qiskit | qiskit | 4,208 | 2,164 | 216 | Python | https://www.ibm.com/quantum/qiskit | Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives. | qiskit | 2024-01-14 | 2017-03-03 | 360 | 11.670365 | https://avatars.githubusercontent.com/u/30696987?v=4 | Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives. | ['qiskit', 'quantum', 'quantum-circuit', 'quantum-computing', 'quantum-programming-language', 'sdk'] | ['qiskit', 'quantum', 'quantum-circuit', 'quantum-computing', 'quantum-programming-language', 'sdk'] | 2024-01-12 | [('jackhidary/quantumcomputingbook', 0.5992211699485779, 'study', 3), ('cqcl/tket', 0.5771373510360718, 'util', 1), ('quantumlib/cirq', 0.5546154975891113, 'sim', 1), ('cqcl/lambeq', 0.5245597958564758, 'nlp', 0), ('netket/netket', 0.5100851058959961, 'sim', 1)] | 534 | 5 | null | 18.23 | 804 | 580 | 84 | 0 | 20 | 16 | 20 | 805 | 1,767 | 90 | 2.2 | 61 |
1,313 | diffusion | https://github.com/idea-research/groundingdino | ['awesome'] | null | [] | [] | null | null | null | idea-research/groundingdino | GroundingDINO | 4,067 | 415 | 30 | Python | https://arxiv.org/abs/2303.05499 | Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection" | idea-research | 2024-01-14 | 2023-03-09 | 46 | 87.061162 | https://avatars.githubusercontent.com/u/113572103?v=4 | Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection" | ['object-detection', 'open-world', 'open-world-detection', 'vision-language', 'vision-language-transformer'] | ['awesome', 'object-detection', 'open-world', 'open-world-detection', 'vision-language', 'vision-language-transformer'] | 2023-12-31 | [('idea-research/grounded-segment-anything', 0.6477982997894287, 'llm', 0), ('roboflow/notebooks', 0.5870379209518433, 'study', 1), ('facebookresearch/dinov2', 0.5680932402610779, 'diffusion', 0), ('nvlabs/gcvit', 0.5644093751907349, 'diffusion', 1), ('open-mmlab/mmdetection', 0.5333415269851685, 'ml', 1), ('deci-ai/super-gradients', 0.5182757377624512, 'ml-dl', 1)] | 23 | 6 | null | 1.25 | 67 | 12 | 10 | 0 | 2 | 2 | 2 | 67 | 67 | 90 | 1 | 61 |
515 | util | https://github.com/spack/spack | [] | null | [] | [] | null | null | null | spack/spack | spack | 3,783 | 2,097 | 100 | Python | https://spack.io | A flexible package manager that supports multiple versions, configurations, platforms, and compilers. | spack | 2024-01-14 | 2014-01-08 | 524 | 7.207676 | https://avatars.githubusercontent.com/u/25539161?v=4 | A flexible package manager that supports multiple versions, configurations, platforms, and compilers. | ['build-tools', 'hpc', 'linux', 'macos', 'package-manager', 'radiuss', 'scientific-computing', 'spack'] | ['build-tools', 'hpc', 'linux', 'macos', 'package-manager', 'radiuss', 'scientific-computing', 'spack'] | 2024-01-13 | [('conda/conda', 0.7269142270088196, 'util', 1), ('mamba-org/mamba', 0.6774295568466187, 'util', 1), ('pomponchik/instld', 0.6380254030227661, 'util', 1), ('pypa/hatch', 0.592124879360199, 'util', 1), ('pypa/setuptools_scm', 0.5813215970993042, 'util', 0), ('mitsuhiko/rye', 0.5651411414146423, 'util', 1), ('pdm-project/pdm', 0.5586650371551514, 'util', 1), ('tiiuae/sbomnix', 0.5559228658676147, 'util', 0), ('indygreg/pyoxidizer', 0.5544406771659851, 'util', 1), ('mtkennerly/dunamai', 0.5440518856048584, 'util', 0), ('python-poetry/poetry', 0.5117734670639038, 'util', 1), ('scikit-build/scikit-build', 0.5056064128875732, 'ml', 0), ('mamba-org/boa', 0.5025382041931152, 'util', 0), ('polyaxon/polyaxon', 0.5023648738861084, 'ml-ops', 0)] | 1,567 | 4 | null | 109.62 | 2,017 | 1,508 | 122 | 0 | 8 | 10 | 8 | 2,016 | 3,672 | 90 | 1.8 | 61 |
1,436 | jupyter | https://github.com/jupyterlab/jupyter-ai | [] | null | [] | [] | null | null | null | jupyterlab/jupyter-ai | jupyter-ai | 2,475 | 225 | 31 | Python | https://jupyter-ai.readthedocs.io/ | A generative AI extension for JupyterLab | jupyterlab | 2024-01-14 | 2023-02-09 | 50 | 48.802817 | https://avatars.githubusercontent.com/u/22800682?v=4 | A generative AI extension for JupyterLab | ['generative-ai', 'jupyter', 'jupyterlab', 'jupyterlab-extension'] | ['generative-ai', 'jupyter', 'jupyterlab', 'jupyterlab-extension'] | 2024-01-10 | [('chaoleili/jupyterlab_tensorboard', 0.5836908221244812, 'jupyter', 2), ('jupyterlab/jupyterlab', 0.5743774771690369, 'jupyter', 2), ('jupyter-lsp/jupyterlab-lsp', 0.5275683403015137, 'jupyter', 3), ('ipython/ipykernel', 0.5044593811035156, 'util', 1), ('jupyter-widgets/ipywidgets', 0.5035024285316467, 'jupyter', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5025471448898315, 'study', 0)] | 19 | 3 | null | 5.04 | 212 | 134 | 11 | 0 | 42 | 156 | 42 | 212 | 354 | 90 | 1.7 | 61 |
1,821 | llm | https://github.com/predibase/lorax | ['fine-tuned', 'scale', 'gpu'] | null | [] | [] | null | null | null | predibase/lorax | lorax | 671 | 52 | 19 | Python | https://predibase.github.io/lorax/ | Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs | predibase | 2024-01-14 | 2023-10-20 | 14 | 46.04902 | https://avatars.githubusercontent.com/u/75280641?v=4 | Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs | ['fine-tuning', 'gpt', 'llama', 'llm', 'llm-inference', 'llm-serving', 'llmops', 'lora', 'model-serving', 'pytorch', 'transformers'] | ['fine-tuned', 'fine-tuning', 'gpt', 'gpu', 'llama', 'llm', 'llm-inference', 'llm-serving', 'llmops', 'lora', 'model-serving', 'pytorch', 'scale', 'transformers'] | 2024-01-11 | [('vllm-project/vllm', 0.7764987945556641, 'llm', 7), ('bentoml/openllm', 0.7207032442092896, 'ml-ops', 6), ('bigscience-workshop/petals', 0.6941356062889099, 'data', 3), ('ray-project/ray-llm', 0.6269615888595581, 'llm', 5), ('intel/intel-extension-for-transformers', 0.5878379940986633, 'perf', 2), ('tairov/llama2.mojo', 0.568372368812561, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5675815939903259, 'llm', 6), ('hiyouga/llama-factory', 0.5675815343856812, 'llm', 6), ('microsoft/jarvis', 0.5660221576690674, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5625096559524536, 'llm', 4), ('sjtu-ipads/powerinfer', 0.5567286014556885, 'llm', 3), ('eugeneyan/open-llms', 0.5560584664344788, 'study', 1), ('bobazooba/xllm', 0.5401611924171448, 'llm', 4), ('run-llama/llama-hub', 0.5340386629104614, 'data', 1), ('jerryjliu/llama_index', 0.5294747352600098, 'llm', 3), ('young-geng/easylm', 0.5218080878257751, 'llm', 1), ('salesforce/xgen', 0.5184742212295532, 'llm', 1), ('jzhang38/tinyllama', 0.5169039964675903, 'llm', 1), ('skypilot-org/skypilot', 0.5144446492195129, 'llm', 2), ('opengenerativeai/genossgpt', 0.5129587650299072, 'llm', 3), ('tloen/alpaca-lora', 0.507797122001648, 'llm', 1), ('titanml/takeoff', 0.50351482629776, 'llm', 2), ('lightning-ai/lit-gpt', 0.5018265247344971, 'llm', 1)] | 40 | 5 | null | 9.62 | 181 | 145 | 3 | 0 | 12 | 53 | 12 | 181 | 318 | 90 | 1.8 | 61 |
91 | web | https://github.com/tornadoweb/tornado | [] | null | [] | ['tornado'] | 1 | null | null | tornadoweb/tornado | tornado | 21,397 | 5,574 | 994 | Python | http://www.tornadoweb.org/ | Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. | tornadoweb | 2024-01-13 | 2009-09-09 | 750 | 28.496766 | https://avatars.githubusercontent.com/u/7468980?v=4 | Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. | ['asynchronous'] | ['asynchronous'] | 2024-01-12 | [('encode/starlette', 0.57993084192276, 'web', 0), ('pallets/quart', 0.5757850408554077, 'web', 0), ('python-trio/trio', 0.5695123076438904, 'perf', 0), ('agronholm/anyio', 0.5639466643333435, 'perf', 0), ('timofurrer/awesome-asyncio', 0.5469016432762146, 'study', 0), ('alirn76/panther', 0.5357459187507629, 'web', 0), ('aio-libs/aiohttp', 0.5350281596183777, 'web', 0), ('sumerc/yappi', 0.5336647629737854, 'profiling', 1), ('masoniteframework/masonite', 0.5226184725761414, 'web', 0), ('neoteroi/blacksheep', 0.5203468203544617, 'web', 0), ('klen/muffin', 0.5200356245040894, 'web', 0), ('airtai/faststream', 0.5190186500549316, 'perf', 0), ('bottlepy/bottle', 0.5174039006233215, 'web', 0), ('encode/httpx', 0.5143762230873108, 'web', 0), ('praw-dev/asyncpraw', 0.5063261389732361, 'ml-dl', 0)] | 438 | 6 | null | 2.12 | 32 | 20 | 175 | 0 | 0 | 5 | 5 | 32 | 29 | 90 | 0.9 | 60 |
176 | util | https://github.com/delgan/loguru | [] | null | [] | [] | 1 | null | null | delgan/loguru | loguru | 17,102 | 690 | 133 | Python | null | Python logging made (stupidly) simple | delgan | 2024-01-14 | 2017-08-15 | 337 | 50.747774 | null | Python logging made (stupidly) simple | ['log', 'logger', 'logging'] | ['log', 'logger', 'logging'] | 2024-01-10 | [('metachris/logzero', 0.7877286672592163, 'util', 1), ('alexmojaki/snoop', 0.5699717998504639, 'debug', 1)] | 52 | 1 | null | 2.1 | 88 | 43 | 78 | 0 | 3 | 3 | 3 | 88 | 183 | 90 | 2.1 | 60 |
1,292 | llm | https://github.com/fauxpilot/fauxpilot | [] | null | [] | [] | null | null | null | fauxpilot/fauxpilot | fauxpilot | 13,782 | 602 | 123 | Python | null | FauxPilot - an open-source alternative to GitHub Copilot server | fauxpilot | 2024-01-14 | 2022-08-03 | 77 | 177.016514 | https://avatars.githubusercontent.com/u/120729571?v=4 | FauxPilot - an open-source alternative to GitHub Copilot server | [] | [] | 2023-05-29 | [('fastai/ghapi', 0.5876653790473938, 'util', 0), ('mozillazg/pypy', 0.5119403004646301, 'util', 0)] | 14 | 6 | null | 0.27 | 11 | 2 | 18 | 8 | 0 | 0 | 0 | 11 | 17 | 90 | 1.5 | 60 |
52 | graph | https://github.com/networkx/networkx | [] | null | [] | [] | null | null | null | networkx/networkx | networkx | 13,757 | 3,154 | 274 | Python | https://networkx.org | Network Analysis in Python | networkx | 2024-01-14 | 2010-09-06 | 699 | 19.676951 | https://avatars.githubusercontent.com/u/388785?v=4 | Network Analysis in Python | ['complex-networks', 'graph-algorithms', 'graph-analysis', 'graph-generation', 'graph-theory', 'graph-visualization', 'spec-0', 'spec-1', 'spec-4'] | ['complex-networks', 'graph-algorithms', 'graph-analysis', 'graph-generation', 'graph-theory', 'graph-visualization', 'spec-0', 'spec-1', 'spec-4'] | 2024-01-13 | [('pygraphviz/pygraphviz', 0.6983128786087036, 'viz', 3), ('graphistry/pygraphistry', 0.6410859823226929, 'data', 1), ('westhealth/pyvis', 0.6360735297203064, 'graph', 0), ('scikit-mobility/scikit-mobility', 0.614628255367279, 'gis', 0), ('artelys/geonetworkx', 0.5718642473220825, 'gis', 0), ('a-r-j/graphein', 0.5483938455581665, 'sim', 0), ('scikit-image/scikit-image', 0.5438209772109985, 'util', 3), ('keon/algorithms', 0.543645977973938, 'util', 0), ('stellargraph/stellargraph', 0.5425050258636475, 'graph', 1), ('kuanb/peartree', 0.532261312007904, 'gis', 0), ('ranaroussi/quantstats', 0.5321804881095886, 'finance', 0), ('h4kor/graph-force', 0.5262413620948792, 'graph', 1), ('plotly/plotly.py', 0.5152801275253296, 'viz', 0), ('thealgorithms/python', 0.5088640451431274, 'study', 0), ('secdev/scapy', 0.5021397471427917, 'util', 0), ('scipy/scipy', 0.5018213391304016, 'math', 0)] | 703 | 2 | null | 7.6 | 303 | 230 | 163 | 0 | 4 | 7 | 4 | 303 | 572 | 90 | 1.9 | 60 |
319 | gui | https://github.com/pysimplegui/pysimplegui | [] | null | [] | [] | 1 | null | null | pysimplegui/pysimplegui | PySimpleGUI | 12,925 | 1,788 | 231 | Python | https://www.PySimpleGUI.com | Launched in 2018. It's 2023 and PySimpleGUI is actively developed & supported. Create complex windows simply. Supports tkinter, Qt, WxPython, Remi (in browser). Create GUI applications trivially with a full set of widgets. Multi-Window applications are also simple. 3.4 to 3.11 supported. 325+ Demo programs & Cookbook for rapid start. Extensive docs | pysimplegui | 2024-01-14 | 2018-07-11 | 289 | 44.590931 | null | Launched in 2018. It's 2023 and PySimpleGUI is actively developed & supported. Create complex windows simply. Supports tkinter, Qt, WxPython, Remi (in browser). Create GUI applications trivially with a full set of widgets. Multi-Window applications are also simple. 3.4 to 3.11 supported. 325+ Demo programs & Cookbook for rapid start. Extensive docs | ['beginner-friendly', 'datavisualization', 'games', 'gui', 'gui-framework', 'gui-programming', 'gui-window', 'pyside2', 'pysimplegui', 'python-gui', 'qt', 'qt-gui', 'remi', 'systemtray', 'tkinter', 'tkinter-gui', 'tkinter-python', 'user-interface', 'wxpython'] | ['beginner-friendly', 'datavisualization', 'games', 'gui', 'gui-framework', 'gui-programming', 'gui-window', 'pyside2', 'pysimplegui', 'python-gui', 'qt', 'qt-gui', 'remi', 'systemtray', 'tkinter', 'tkinter-gui', 'tkinter-python', 'user-interface', 'wxpython'] | 2023-11-26 | [('parthjadhav/tkinter-designer', 0.7242632508277893, 'gui', 4), ('wxwidgets/phoenix', 0.703073263168335, 'gui', 3), ('hoffstadt/dearpygui', 0.6711195111274719, 'gui', 2), ('r0x0r/pywebview', 0.6416908502578735, 'gui', 2), ('pyglet/pyglet', 0.624721884727478, 'gamedev', 0), ('beeware/toga', 0.6206801533699036, 'gui', 1), ('kivy/kivy', 0.600288450717926, 'util', 0), ('willmcgugan/textual', 0.589139997959137, 'term', 0), ('holoviz/panel', 0.5573893189430237, 'viz', 1), ('pypy/pypy', 0.5493513345718384, 'util', 0), ('jupyter-widgets/ipywidgets', 0.5297706127166748, 'jupyter', 0), ('urwid/urwid', 0.5266430974006653, 'term', 0), ('bokeh/bokeh', 0.5222162008285522, 'viz', 0), ('masoniteframework/masonite', 0.5136278867721558, 'web', 0), ('matplotlib/matplotlib', 0.5119383931159973, 'viz', 1), ('maartenbreddels/ipyvolume', 0.5105063319206238, 'jupyter', 0), ('voila-dashboards/voila', 0.5095065236091614, 'jupyter', 0), ('plotly/dash', 0.5075579285621643, 'viz', 1)] | 18 | 4 | null | 2.46 | 134 | 89 | 67 | 2 | 2 | 1 | 2 | 134 | 455 | 90 | 3.4 | 60 |
174 | term | https://github.com/tiangolo/typer | [] | null | [] | [] | 1 | null | null | tiangolo/typer | typer | 12,834 | 521 | 69 | Python | https://typer.tiangolo.com/ | Typer, build great CLIs. Easy to code. Based on Python type hints. | tiangolo | 2024-01-14 | 2019-12-24 | 214 | 59.971963 | null | Typer, build great CLIs. Easy to code. Based on Python type hints. | ['cli', 'click', 'shell', 'terminal', 'typehints', 'typer'] | ['cli', 'click', 'shell', 'terminal', 'typehints', 'typer'] | 2023-12-10 | [('pyscript/pyscript-cli', 0.6438218355178833, 'web', 0), ('kellyjonbrazil/jc', 0.6338556408882141, 'util', 1), ('xonsh/xonsh', 0.614140510559082, 'util', 3), ('google/python-fire', 0.6071035265922546, 'term', 1), ('jquast/blessed', 0.5800941586494446, 'term', 2), ('python-poetry/cleo', 0.5780348777770996, 'term', 1), ('facebook/pyre-check', 0.5768271088600159, 'typing', 0), ('textualize/trogon', 0.5765345692634583, 'term', 3), ('tmbo/questionary', 0.5755541324615479, 'term', 1), ('pytoolz/toolz', 0.5614187121391296, 'util', 0), ('landscapeio/prospector', 0.558975100517273, 'util', 0), ('willmcgugan/rich', 0.5575374364852905, 'term', 1), ('python/cpython', 0.5462526082992554, 'util', 0), ('google/pytype', 0.5461122393608093, 'typing', 0), ('python/mypy', 0.5458303093910217, 'typing', 0), ('urwid/urwid', 0.5432376861572266, 'term', 0), ('astral-sh/ruff', 0.5375232100486755, 'util', 0), ('methexis-inc/terminal-copilot', 0.5327745079994202, 'util', 0), ('pexpect/pexpect', 0.5308032035827637, 'util', 0), ('pypy/pypy', 0.5274914503097534, 'util', 0), ('typesense/typesense-python', 0.5246941447257996, 'data', 0), ('agronholm/typeguard', 0.5242935419082642, 'typing', 0), ('hhatto/autopep8', 0.5092093348503113, 'util', 0), ('evhub/coconut', 0.5052512884140015, 'util', 0)] | 37 | 4 | null | 0.62 | 58 | 15 | 49 | 1 | 2 | 6 | 2 | 58 | 108 | 90 | 1.9 | 60 |
1,106 | data | https://github.com/redis/redis-py | [] | null | [] | [] | null | null | null | redis/redis-py | redis-py | 11,993 | 2,483 | 324 | Python | null | Redis Python Client | redis | 2024-01-13 | 2009-11-06 | 742 | 16.150635 | https://avatars.githubusercontent.com/u/1529926?v=4 | Redis Python Client | ['redis', 'redis-client', 'redis-cluster', 'redis-py'] | ['redis', 'redis-client', 'redis-cluster', 'redis-py'] | 2024-01-11 | [] | 429 | 7 | null | 3.37 | 174 | 101 | 173 | 0 | 21 | 7 | 21 | 174 | 183 | 90 | 1.1 | 60 |
520 | diffusion | https://github.com/lucidrains/dalle2-pytorch | [] | null | [] | [] | null | null | null | lucidrains/dalle2-pytorch | DALLE2-pytorch | 10,534 | 1,032 | 127 | Python | null | Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch | lucidrains | 2024-01-14 | 2022-04-07 | 94 | 111.218703 | null | Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch | ['artificial-intelligence', 'deep-learning', 'text-to-image'] | ['artificial-intelligence', 'deep-learning', 'text-to-image'] | 2023-10-19 | [('lucidrains/imagen-pytorch', 0.7950653433799744, 'ml-dl', 3), ('lucidrains/deep-daze', 0.631841242313385, 'ml', 3), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.6031858325004578, 'web', 1), ('saharmor/dalle-playground', 0.5927163362503052, 'diffusion', 2), ('openai/glide-text2im', 0.5790383219718933, 'diffusion', 0), ('sharonzhou/long_stable_diffusion', 0.5584306120872498, 'diffusion', 0), ('salesforce/blip', 0.5417680740356445, 'diffusion', 0), ('pytorch/ignite', 0.5412147641181946, 'ml-dl', 1), ('minimaxir/gpt-2-simple', 0.5398170948028564, 'llm', 0), ('minimaxir/textgenrnn', 0.5387126207351685, 'nlp', 1), ('pytorch-labs/gpt-fast', 0.5372596383094788, 'llm', 0), ('skorch-dev/skorch', 0.5362039804458618, 'ml-dl', 0), ('allenai/allennlp', 0.5331498384475708, 'nlp', 1), ('huggingface/diffusers', 0.532724142074585, 'diffusion', 1), ('hysts/pytorch_image_classification', 0.519826352596283, 'ml-dl', 0), ('alibaba/easynlp', 0.5197792649269104, 'nlp', 1), ('yoadtew/zero-shot-image-to-text', 0.5140002965927124, 'nlp', 0), ('laion-ai/dalle2-laion', 0.5131522417068481, 'diffusion', 1), ('open-mmlab/mmediting', 0.5127325654029846, 'ml', 1), ('denys88/rl_games', 0.5112625956535339, 'ml-rl', 1), ('google-research/electra', 0.5081148743629456, 'ml-dl', 1), ('intel/intel-extension-for-pytorch', 0.5061784982681274, 'perf', 1), ('nvlabs/gcvit', 0.5059126019477844, 'diffusion', 1), ('infinitylogesh/mutate', 0.5058514475822449, 'nlp', 0), ('karpathy/micrograd', 0.5032515525817871, 'study', 0)] | 17 | 2 | null | 0.29 | 12 | 1 | 22 | 3 | 13 | 195 | 13 | 12 | 25 | 90 | 2.1 | 60 |
700 | sim | https://github.com/isl-org/open3d | [] | null | [] | [] | null | null | null | isl-org/open3d | Open3D | 9,977 | 2,140 | 197 | C++ | http://www.open3d.org | Open3D: A Modern Library for 3D Data Processing | isl-org | 2024-01-13 | 2016-12-02 | 373 | 26.707075 | https://avatars.githubusercontent.com/u/23507030?v=4 | Open3D: A Modern Library for 3D Data Processing | ['3d', '3d-perception', 'arm', 'computer-graphics', 'cpp', 'cuda', 'gpu', 'gui', 'machine-learning', 'mesh-processing', 'odometry', 'opengl', 'pointcloud', 'pytorch', 'reconstruction', 'registration', 'rendering', 'tensorflow', 'visualization'] | ['3d', '3d-perception', 'arm', 'computer-graphics', 'cpp', 'cuda', 'gpu', 'gui', 'machine-learning', 'mesh-processing', 'odometry', 'opengl', 'pointcloud', 'pytorch', 'reconstruction', 'registration', 'rendering', 'tensorflow', 'visualization'] | 2024-01-05 | [('facebookresearch/pytorch3d', 0.634926438331604, 'ml-dl', 0), ('kornia/kornia', 0.6128343939781189, 'ml-dl', 2), ('marcomusy/vedo', 0.6037029027938843, 'viz', 2), ('pyvista/pyvista', 0.5594555735588074, 'viz', 3), ('pokepetter/ursina', 0.5535932183265686, 'gamedev', 0), ('earthlab/earthpy', 0.5324108004570007, 'gis', 0), ('panda3d/panda3d', 0.5318998694419861, 'gamedev', 1), ('google/tf-quant-finance', 0.5206282138824463, 'finance', 2), ('dfki-ric/pytransform3d', 0.5204105377197266, 'math', 1), ('tensorlayer/tensorlayer', 0.5200856328010559, 'ml-rl', 1), ('polyaxon/datatile', 0.5179375410079956, 'pandas', 2), ('roboflow/supervision', 0.5120977759361267, 'ml', 3), ('raphaelquast/eomaps', 0.5115019679069519, 'gis', 1), ('geomstats/geomstats', 0.5070082545280457, 'math', 1), ('blackhc/toma', 0.5056933164596558, 'ml-dl', 3), ('domlysz/blendergis', 0.5055702924728394, 'gis', 1), ('cvxgrp/pymde', 0.5052924156188965, 'ml', 5), ('cupy/cupy', 0.5012453198432922, 'math', 2)] | 217 | 6 | null | 2.29 | 280 | 120 | 87 | 0 | 2 | 3 | 2 | 280 | 370 | 90 | 1.3 | 60 |
1,446 | testing | https://github.com/microsoft/playwright-python | ['automation'] | null | [] | [] | null | null | null | microsoft/playwright-python | playwright-python | 9,951 | 845 | 127 | Python | https://playwright.dev/python/ | Python version of the Playwright testing and automation library. | microsoft | 2024-01-14 | 2020-07-01 | 186 | 53.254587 | https://avatars.githubusercontent.com/u/6154722?v=4 | Python version of the Playwright testing and automation library. | ['chromium', 'firefox', 'playwright', 'webkit'] | ['automation', 'chromium', 'firefox', 'playwright', 'webkit'] | 2024-01-10 | [('seleniumbase/seleniumbase', 0.6941218972206116, 'testing', 2), ('cobrateam/splinter', 0.6916419267654419, 'testing', 1), ('masoniteframework/masonite', 0.549170970916748, 'web', 0), ('pexpect/pexpect', 0.5341052412986755, 'util', 1), ('r0x0r/pywebview', 0.5271952748298645, 'gui', 1), ('pyscript/pyscript-cli', 0.5237164497375488, 'web', 0), ('pytoolz/toolz', 0.5224789977073669, 'util', 0), ('eleutherai/pyfra', 0.5212807059288025, 'ml', 0), ('amaargiru/pyroad', 0.5205329060554504, 'study', 0), ('pytest-dev/pytest-bdd', 0.5180904865264893, 'testing', 0), ('pyscript/pyscript', 0.5149538516998291, 'web', 0), ('pyodide/pyodide', 0.5146863460540771, 'util', 0), ('nedbat/coveragepy', 0.5143460631370544, 'testing', 0), ('bokeh/bokeh', 0.510855495929718, 'viz', 0), ('urwid/urwid', 0.5090146660804749, 'term', 0), ('willmcgugan/textual', 0.5054807662963867, 'term', 0), ('webpy/webpy', 0.505174994468689, 'web', 0), ('hoffstadt/dearpygui', 0.5034270882606506, 'gui', 0)] | 35 | 1 | null | 1.88 | 140 | 122 | 43 | 0 | 13 | 23 | 13 | 139 | 190 | 90 | 1.4 | 60 |
53 | perf | https://github.com/numba/numba | [] | null | [] | [] | null | null | null | numba/numba | numba | 9,159 | 1,130 | 200 | Python | http://numba.pydata.org/ | NumPy aware dynamic Python compiler using LLVM | numba | 2024-01-13 | 2012-03-08 | 620 | 14.755581 | https://avatars.githubusercontent.com/u/1628082?v=4 | NumPy aware dynamic Python compiler using LLVM | ['compiler', 'cuda', 'llvm', 'numpy', 'parallel'] | ['compiler', 'cuda', 'llvm', 'numpy', 'parallel'] | 2023-12-14 | [('exaloop/codon', 0.7364824414253235, 'perf', 2), ('google/jax', 0.6459792256355286, 'ml', 1), ('lcompilers/lpython', 0.603155255317688, 'util', 1), ('numba/llvmlite', 0.5931792855262756, 'util', 0), ('nvidia/tensorrt-llm', 0.5688282251358032, 'viz', 0), ('ipython/ipyparallel', 0.5564903020858765, 'perf', 1), ('cupy/cupy', 0.555233895778656, 'math', 2), ('nvidia/cuda-python', 0.5387571454048157, 'ml', 0), ('micropython/micropython', 0.5256375670433044, 'util', 0), ('pypy/pypy', 0.5218566656112671, 'util', 1), ('numpy/numpy', 0.5208587050437927, 'math', 1), ('hips/autograd', 0.5151181817054749, 'ml', 0), ('cython/cython', 0.504206120967865, 'util', 0)] | 364 | 4 | null | 30.42 | 265 | 127 | 144 | 1 | 4 | 17 | 4 | 265 | 598 | 90 | 2.3 | 60 |
10 | util | https://github.com/cython/cython | [] | null | [] | [] | null | null | null | cython/cython | cython | 8,636 | 1,516 | 240 | Python | https://cython.org | The most widely used Python to C compiler | cython | 2024-01-14 | 2010-11-21 | 688 | 12.547115 | https://avatars.githubusercontent.com/u/486082?v=4 | The most widely used Python to C compiler | ['big-data', 'c', 'cpp', 'cpython', 'cpython-extensions', 'cython', 'performance'] | ['big-data', 'c', 'cpp', 'cpython', 'cpython-extensions', 'cython', 'performance'] | 2024-01-12 | [('pypy/pypy', 0.8010214567184448, 'util', 1), ('exaloop/codon', 0.7081640958786011, 'perf', 0), ('python/cpython', 0.6992247700691223, 'util', 1), ('pyston/pyston', 0.6975716352462769, 'util', 0), ('lcompilers/lpython', 0.6913489699363708, 'util', 0), ('scikit-build/scikit-build', 0.6388826966285706, 'ml', 3), ('fastai/fastcore', 0.6373258829116821, 'util', 0), ('faster-cpython/tools', 0.6359994411468506, 'perf', 1), ('pytoolz/toolz', 0.5866791605949402, 'util', 0), ('micropython/micropython', 0.5850077271461487, 'util', 0), ('klen/py-frameworks-bench', 0.5801135301589966, 'perf', 0), ('faster-cpython/ideas', 0.5725173354148865, 'perf', 1), ('libtcod/python-tcod', 0.5713533759117126, 'gamedev', 0), ('joblib/joblib', 0.5678399801254272, 'util', 0), ('intel/intel-extension-for-pytorch', 0.5606357455253601, 'perf', 0), ('pandas-dev/pandas', 0.5577985048294067, 'pandas', 0), ('dylanhogg/awesome-python', 0.5576968193054199, 'study', 0), ('plasma-umass/scalene', 0.5566608905792236, 'profiling', 0), ('pyinfra-dev/pyinfra', 0.5551347732543945, 'util', 0), ('eleutherai/pyfra', 0.5548232793807983, 'ml', 0), ('spotify/annoy', 0.5542510151863098, 'ml', 0), ('ibis-project/ibis', 0.553461492061615, 'data', 0), ('krzjoa/awesome-python-data-science', 0.5530298352241516, 'study', 0), ('facebookincubator/cinder', 0.5495518445968628, 'perf', 1), ('pytables/pytables', 0.549433171749115, 'data', 0), ('hoffstadt/dearpygui', 0.5458163619041443, 'gui', 1), ('ipython/ipyparallel', 0.5451430678367615, 'perf', 0), ('pympler/pympler', 0.5429266691207886, 'perf', 0), ('pypa/hatch', 0.5406709313392639, 'util', 0), ('panda3d/panda3d', 0.5402704477310181, 'gamedev', 0), ('rustpython/rustpython', 0.5352054238319397, 'util', 0), ('google/jax', 0.5345306992530823, 'ml', 0), ('ultrajson/ultrajson', 0.5291088223457336, 'perf', 1), ('markshannon/faster-cpython', 0.5285276770591736, 'perf', 0), ('willmcgugan/textual', 0.52788907289505, 'term', 0), ('fredrik-johansson/mpmath', 0.527232825756073, 'math', 0), ('wesm/pydata-book', 0.5262758135795593, 'study', 0), ('pytoolz/cytoolz', 0.5252465009689331, 'util', 0), ('vaexio/vaex', 0.5234464406967163, 'perf', 0), ('scikit-hep/uproot5', 0.5226044058799744, 'data', 1), ('google/tf-quant-finance', 0.5225537419319153, 'finance', 0), ('numba/llvmlite', 0.5224786996841431, 'util', 0), ('adafruit/circuitpython', 0.5219005346298218, 'util', 1), ('fchollet/deep-learning-with-python-notebooks', 0.5218517780303955, 'study', 0), ('1200wd/bitcoinlib', 0.5212488770484924, 'crypto', 0), ('rubik/radon', 0.5208148956298828, 'util', 0), ('pytorch/glow', 0.5203021168708801, 'ml', 0), ('backtick-se/cowait', 0.5182483792304993, 'util', 0), ('timofurrer/awesome-asyncio', 0.5178491473197937, 'study', 0), ('pyo3/maturin', 0.5176377892494202, 'util', 1), ('samuelcolvin/python-devtools', 0.5175613164901733, 'debug', 0), ('dosisod/refurb', 0.5158920288085938, 'util', 0), ('thealgorithms/python', 0.5155187249183655, 'study', 0), ('p403n1x87/austin', 0.5145069360733032, 'profiling', 1), ('numpy/numpy', 0.5139519572257996, 'math', 0), ('eventual-inc/daft', 0.5138062238693237, 'pandas', 0), ('crunch-io/lazycsv', 0.5136982202529907, 'perf', 0), ('ipython/ipython', 0.5134088397026062, 'util', 0), ('pythonspeed/filprofiler', 0.5108945369720459, 'profiling', 0), ('pythonprofilers/memory_profiler', 0.5089790225028992, 'profiling', 0), ('sumerc/yappi', 0.5085721611976624, 'profiling', 1), ('lukaszahradnik/pyneuralogic', 0.5075069665908813, 'math', 0), ('connorferster/handcalcs', 0.5067312121391296, 'jupyter', 0), ('wxwidgets/phoenix', 0.5055117011070251, 'gui', 0), ('grantjenks/blue', 0.5051524043083191, 'util', 0), ('xonsh/xonsh', 0.5044435262680054, 'util', 0), ('numba/numba', 0.504206120967865, 'perf', 0), ('goldmansachs/gs-quant', 0.5038447380065918, 'finance', 0), ('openai/triton', 0.502590537071228, 'util', 0), ('tobymao/sqlglot', 0.5022580623626709, 'data', 0), ('facebook/pyre-check', 0.5014179944992065, 'typing', 0), ('imageio/imageio', 0.5013166666030884, 'util', 0), ('urwid/urwid', 0.5010424852371216, 'term', 0)] | 516 | 4 | null | 14.48 | 262 | 160 | 160 | 0 | 19 | 15 | 19 | 262 | 591 | 90 | 2.3 | 60 |
7 | util | https://github.com/boto/boto3 | [] | null | [] | [] | null | null | null | boto/boto3 | boto3 | 8,518 | 1,865 | 241 | Python | https://aws.amazon.com/sdk-for-python/ | AWS SDK for Python | boto | 2024-01-13 | 2014-10-03 | 486 | 17.506166 | https://avatars.githubusercontent.com/u/327752?v=4 | AWS SDK for Python | ['aws', 'aws-sdk', 'cloud', 'cloud-management'] | ['aws', 'aws-sdk', 'cloud', 'cloud-management'] | 2024-01-14 | [('samuelcolvin/aioaws', 0.6758776307106018, 'data', 1), ('aws/chalice', 0.66681307554245, 'web', 2), ('nficano/python-lambda', 0.6395252346992493, 'util', 1), ('aws/aws-lambda-python-runtime-interface-client', 0.6017659902572632, 'util', 0), ('jordaneremieff/mangum', 0.589402973651886, 'web', 1), ('awslabs/python-deequ', 0.5848604440689087, 'ml', 1), ('geeogi/async-python-lambda-template', 0.5832446813583374, 'template', 0), ('pynamodb/pynamodb', 0.5776386857032776, 'data', 1), ('drivendataorg/cloudpathlib', 0.5708515644073486, 'data', 0), ('backtick-se/cowait', 0.5623748302459717, 'util', 0), ('localstack/localstack', 0.5544808506965637, 'util', 2), ('aws-samples/sagemaker-ssh-helper', 0.5350908637046814, 'util', 1), ('aws/aws-sdk-pandas', 0.5303450226783752, 'pandas', 1), ('sentinel-hub/sentinelhub-py', 0.5275383591651917, 'gis', 1), ('prefecthq/prefect-aws', 0.5230756402015686, 'data', 1), ('amzn/ion-python', 0.5133451223373413, 'data', 0)] | 153 | 4 | null | 10.52 | 155 | 119 | 113 | 0 | 0 | 158 | 158 | 155 | 286 | 90 | 1.8 | 60 |
71 | ml | https://github.com/pymc-devs/pymc3 | [] | null | [] | [] | null | null | null | pymc-devs/pymc3 | pymc | 7,970 | 1,914 | 227 | Python | https://docs.pymc.io/ | Bayesian Modeling and Probabilistic Programming in Python | pymc-devs | 2024-01-13 | 2009-05-05 | 769 | 10.364109 | https://avatars.githubusercontent.com/u/81121?v=4 | Bayesian Modeling and Probabilistic Programming in Python | ['bayesian-inference', 'mcmc', 'probabilistic-programming', 'pytensor', 'statistical-analysis', 'variational-inference'] | ['bayesian-inference', 'mcmc', 'probabilistic-programming', 'pytensor', 'statistical-analysis', 'variational-inference'] | 2024-01-12 | [('pyro-ppl/pyro', 0.6964523792266846, 'ml-dl', 3), ('probml/pyprobml', 0.6565049886703491, 'ml', 1), ('crflynn/stochastic', 0.6376107335090637, 'sim', 0), ('uber/orbit', 0.6276130080223083, 'time-series', 1), ('bayesianmodelingandcomputationinpython/bookcode_edition1', 0.6229053735733032, 'study', 0), ('scikit-learn/scikit-learn', 0.6052919030189514, 'ml', 0), ('awslabs/gluonts', 0.593370795249939, 'time-series', 0), ('infer-actively/pymdp', 0.5866931080818176, 'ml', 0), ('scikit-optimize/scikit-optimize', 0.5821582674980164, 'ml', 0), ('guyallard/markov_clustering', 0.5610766410827637, 'graph', 0), ('stan-dev/pystan', 0.5608965158462524, 'ml', 0), ('statsmodels/statsmodels', 0.5598034858703613, 'ml', 0), ('quantopian/pyfolio', 0.5452370047569275, 'finance', 0), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5400987863540649, 'study', 0), ('pytorch/botorch', 0.5349946618080139, 'ml-dl', 0), ('artemyk/dynpy', 0.5243752002716064, 'sim', 0), ('eleutherai/pyfra', 0.5232195854187012, 'ml', 0), ('sympy/sympy', 0.5158290863037109, 'math', 0), ('goldmansachs/gs-quant', 0.5136345028877258, 'finance', 0), ('selfexplainml/piml-toolbox', 0.5050045847892761, 'ml-interpretability', 0), ('gerdm/prml', 0.5029430985450745, 'study', 0), ('pyomo/pyomo', 0.5023778080940247, 'math', 0)] | 474 | 6 | null | 6.98 | 191 | 99 | 179 | 0 | 25 | 6 | 25 | 191 | 573 | 90 | 3 | 60 |
1,317 | ml-dl | https://github.com/facebookresearch/imagebind | ['pytorch', 'multimodal', 'embeddings'] | null | [] | [] | null | null | null | facebookresearch/imagebind | ImageBind | 7,541 | 666 | 100 | Python | null | ImageBind One Embedding Space to Bind Them All | facebookresearch | 2024-01-13 | 2023-03-23 | 44 | 168.648562 | https://avatars.githubusercontent.com/u/16943930?v=4 | ImageBind One Embedding Space to Bind Them All | [] | ['embeddings', 'multimodal', 'pytorch'] | 2023-11-29 | [] | 15 | 6 | null | 0.37 | 20 | 5 | 10 | 2 | 0 | 0 | 0 | 20 | 16 | 90 | 0.8 | 60 |
1,070 | llm | https://github.com/nvidia/megatron-lm | [] | null | [] | [] | null | null | null | nvidia/megatron-lm | Megatron-LM | 7,504 | 1,701 | 143 | Python | null | Ongoing research training transformer models at scale | nvidia | 2024-01-13 | 2019-03-21 | 253 | 29.576577 | https://avatars.githubusercontent.com/u/1728152?v=4 | Ongoing research training transformer models at scale | [] | [] | 2024-01-12 | [('bigscience-workshop/megatron-deepspeed', 0.6671424508094788, 'llm', 0), ('microsoft/megatron-deepspeed', 0.6671424508094788, 'llm', 0), ('alignmentresearch/tuned-lens', 0.6293410658836365, 'ml-interpretability', 0), ('eleutherai/knowledge-neurons', 0.5722100138664246, 'ml-interpretability', 0), ('karpathy/mingpt', 0.5354270935058594, 'llm', 0), ('lvwerra/trl', 0.5321753025054932, 'llm', 0), ('opengeos/earthformer', 0.507581353187561, 'gis', 0), ('huggingface/optimum', 0.501192569732666, 'ml', 0)] | 118 | 2 | null | 21.87 | 185 | 45 | 59 | 0 | 3 | 4 | 3 | 184 | 288 | 90 | 1.6 | 60 |
1,554 | util | https://github.com/kellyjonbrazil/jc | ['serialization', 'jq'] | null | [] | [] | null | null | null | kellyjonbrazil/jc | jc | 7,298 | 180 | 29 | Python | null | CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts. | kellyjonbrazil | 2024-01-14 | 2019-10-15 | 224 | 32.580357 | null | CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts. | ['bash', 'bash-scripting', 'cli', 'command-line', 'command-line-interface', 'command-line-tool', 'convert', 'json', 'linux', 'parsers', 'scripting', 'serialize', 'shell-scripting', 'yaml'] | ['bash', 'bash-scripting', 'cli', 'command-line', 'command-line-interface', 'command-line-tool', 'convert', 'jq', 'json', 'linux', 'parsers', 'scripting', 'serialization', 'serialize', 'shell-scripting', 'yaml'] | 2023-12-21 | [('kellyjonbrazil/jello', 0.7774760127067566, 'util', 10), ('google/python-fire', 0.6432965397834778, 'term', 1), ('tiangolo/typer', 0.6338556408882141, 'term', 1), ('python-poetry/cleo', 0.6012207269668579, 'term', 2), ('pyscript/pyscript-cli', 0.5959556102752686, 'web', 0), ('xonsh/xonsh', 0.5756747722625732, 'util', 3), ('thoth-station/micropipenv', 0.5520144701004028, 'util', 0), ('deeplook/sparklines', 0.529207170009613, 'term', 1), ('wandb/client', 0.5254802703857422, 'ml', 0), ('samuelcolvin/python-devtools', 0.5224640369415283, 'debug', 0), ('python-odin/odin', 0.5191496014595032, 'util', 3), ('hadialqattan/pycln', 0.5115851163864136, 'util', 0), ('urwid/urwid', 0.5103952884674072, 'term', 0), ('jquast/blessed', 0.5097572207450867, 'term', 1), ('nteract/papermill', 0.5040388703346252, 'jupyter', 0), ('pytoolz/toolz', 0.503423810005188, 'util', 0)] | 41 | 2 | null | 4.48 | 76 | 51 | 52 | 1 | 8 | 25 | 8 | 76 | 287 | 90 | 3.8 | 60 |
279 | nlp | https://github.com/maartengr/bertopic | [] | null | [] | [] | null | null | null | maartengr/bertopic | BERTopic | 5,143 | 647 | 48 | Python | https://maartengr.github.io/BERTopic/ | Leveraging BERT and c-TF-IDF to create easily interpretable topics. | maartengr | 2024-01-13 | 2020-09-22 | 175 | 29.388571 | null | Leveraging BERT and c-TF-IDF to create easily interpretable topics. | ['bert', 'ldavis', 'machine-learning', 'nlp', 'sentence-embeddings', 'topic', 'topic-modeling', 'topic-modelling', 'topic-models', 'transformers'] | ['bert', 'ldavis', 'machine-learning', 'nlp', 'sentence-embeddings', 'topic', 'topic-modeling', 'topic-modelling', 'topic-models', 'transformers'] | 2024-01-10 | [('ddangelov/top2vec', 0.6046782732009888, 'nlp', 3), ('paddlepaddle/paddlenlp', 0.6038503050804138, 'llm', 3), ('jonasgeiping/cramming', 0.5925445556640625, 'nlp', 1), ('rare-technologies/gensim', 0.5905485153198242, 'nlp', 3), ('sebischair/lbl2vec', 0.5893922448158264, 'nlp', 2), ('alibaba/easynlp', 0.5850814580917358, 'nlp', 4), ('llmware-ai/llmware', 0.5808184742927551, 'llm', 4), ('deepset-ai/farm', 0.5806211233139038, 'nlp', 2), ('extreme-bert/extreme-bert', 0.5704385042190552, 'llm', 3), ('graykode/nlp-tutorial', 0.5367704629898071, 'study', 2), ('huggingface/text-generation-inference', 0.5277509093284607, 'llm', 1), ('koaning/whatlies', 0.5192699432373047, 'nlp', 1), ('jalammar/ecco', 0.5192667841911316, 'ml-interpretability', 1), ('norskregnesentral/skweak', 0.5178706645965576, 'nlp', 0), ('flairnlp/flair', 0.5175113677978516, 'nlp', 2), ('qanastek/drbert', 0.51610267162323, 'llm', 3), ('huggingface/transformers', 0.5144845843315125, 'nlp', 3), ('maartengr/keybert', 0.5103285908699036, 'nlp', 1), ('jina-ai/clip-as-service', 0.5079023838043213, 'nlp', 1), ('bigscience-workshop/biomedical', 0.5077448487281799, 'data', 0), ('explosion/spacy-llm', 0.507010817527771, 'llm', 2), ('jina-ai/finetuner', 0.5031505227088928, 'ml', 1)] | 50 | 4 | null | 1.29 | 185 | 94 | 40 | 0 | 4 | 9 | 4 | 185 | 603 | 90 | 3.3 | 60 |
722 | ml-dl | https://github.com/mosaicml/composer | [] | null | [] | [] | null | null | null | mosaicml/composer | composer | 4,781 | 384 | 48 | Python | http://docs.mosaicml.com | Supercharge Your Model Training | mosaicml | 2024-01-13 | 2021-10-12 | 120 | 39.841667 | https://avatars.githubusercontent.com/u/75143706?v=4 | Supercharge Your Model Training | ['deep-learning', 'machine-learning', 'ml-efficiency', 'ml-systems', 'ml-training', 'neural-network', 'neural-networks', 'pytorch'] | ['deep-learning', 'machine-learning', 'ml-efficiency', 'ml-systems', 'ml-training', 'neural-network', 'neural-networks', 'pytorch'] | 2024-01-14 | [('ddbourgin/numpy-ml', 0.6701366305351257, 'ml', 2), ('huggingface/datasets', 0.6692463159561157, 'nlp', 3), ('keras-team/keras', 0.6608446836471558, 'ml-dl', 4), ('onnx/onnx', 0.6314774751663208, 'ml', 4), ('explosion/thinc', 0.6281270980834961, 'ml-dl', 3), ('neuralmagic/sparseml', 0.6215312480926514, 'ml-dl', 1), ('tensorflow/tensorflow', 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709 | ml-ops | https://github.com/flyteorg/flyte | [] | null | [] | [] | null | null | null | flyteorg/flyte | flyte | 4,341 | 460 | 261 | Go | https://flyte.org | Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks. | flyteorg | 2024-01-14 | 2019-10-21 | 223 | 19.453905 | https://avatars.githubusercontent.com/u/35380635?v=4 | Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks. | ['data', 'data-analysis', 'data-science', 'dataops', 'declarative', 'fine-tuning', 'flyte', 'golang', 'grpc', 'kubernetes', 'kubernetes-operator', 'llm', 'machine-learning', 'mlops', 'orchestration-engine', 'production', 'production-grade', 'scale', 'workflow'] | ['data', 'data-analysis', 'data-science', 'dataops', 'declarative', 'fine-tuning', 'flyte', 'golang', 'grpc', 'kubernetes', 'kubernetes-operator', 'llm', 'machine-learning', 'mlops', 'orchestration-engine', 'production', 'production-grade', 'scale', 'workflow'] | 2024-01-12 | [('kestra-io/kestra', 0.7973306775093079, 'ml-ops', 2), ('dagster-io/dagster', 0.7850085496902466, 'ml-ops', 3), ('bodywork-ml/bodywork-core', 0.6820202469825745, 'ml-ops', 4), ('polyaxon/polyaxon', 0.6784146428108215, 'ml-ops', 5), ('mage-ai/mage-ai', 0.6692841053009033, 'ml-ops', 3), ('apache/airflow', 0.6581413745880127, 'ml-ops', 4), ('orchest/orchest', 0.6491807699203491, 'ml-ops', 3), ('prefecthq/prefect', 0.6408464312553406, 'ml-ops', 3), ('getindata/kedro-kubeflow', 0.6279534697532654, 'ml-ops', 1), ('kubeflow/pipelines', 0.6268972754478455, 'ml-ops', 4), ('airbytehq/airbyte', 0.6267026662826538, 'data', 2), ('backtick-se/cowait', 0.6116994023323059, 'util', 2), ('netflix/metaflow', 0.608452320098877, 'ml-ops', 4), ('prefecthq/server', 0.6038605570793152, 'util', 1), ('avaiga/taipy', 0.6026946902275085, 'data', 2), ('meltano/meltano', 0.5828467607498169, 'ml-ops', 2), ('lithops-cloud/lithops', 0.5794029235839844, 'ml-ops', 1), ('ploomber/ploomber', 0.5782303214073181, 'ml-ops', 4), ('zenml-io/zenml', 0.5718936324119568, 'ml-ops', 5), ('astronomer/astro-sdk', 0.5711103081703186, 'ml-ops', 2), ('kubeflow-kale/kale', 0.5685352683067322, 'ml-ops', 1), ('skypilot-org/skypilot', 0.5598949790000916, 'llm', 2), ('chaostoolkit/chaostoolkit', 0.5509274005889893, 'util', 0), ('fugue-project/fugue', 0.5496802926063538, 'pandas', 1), ('dagworks-inc/hamilton', 0.549081027507782, 'ml-ops', 4), ('allegroai/clearml', 0.5446012616157532, 'ml-ops', 2), ('merantix-momentum/squirrel-core', 0.5294408798217773, 'ml', 3), ('gefyrahq/gefyra', 0.5291821956634521, 'util', 1), ('spotify/luigi', 0.5278602242469788, 'ml-ops', 0), ('modin-project/modin', 0.5223826169967651, 'perf', 1), ('apache/spark', 0.5193337202072144, 'data', 0), ('unionai-oss/unionml', 0.5188993215560913, 'ml-ops', 2), ('tiangolo/full-stack-fastapi-postgresql', 0.5061784386634827, 'template', 0), ('pathwaycom/pathway', 0.503392219543457, 'data', 0), ('featureform/embeddinghub', 0.5021466612815857, 'nlp', 3), ('polyaxon/datatile', 0.5018032789230347, 'pandas', 3), ('bentoml/bentoml', 0.5007025599479675, 'ml-ops', 3)] | 198 | 4 | null | 11.79 | 1,217 | 503 | 52 | 0 | 21 | 106 | 21 | 1,213 | 1,310 | 90 | 1.1 | 60 |
440 | gis | https://github.com/osgeo/gdal | [] | null | [] | [] | null | null | null | osgeo/gdal | gdal | 4,275 | 2,286 | 167 | C++ | https://gdal.org | GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats. | osgeo | 2024-01-13 | 2012-10-09 | 590 | 7.245763 | https://avatars.githubusercontent.com/u/1058467?v=4 | GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats. | ['geospatial-data', 'raster', 'remote-sensing', 'vector'] | ['geospatial-data', 'raster', 'remote-sensing', 'vector'] | 2024-01-13 | [('remotesensinglab/raster4ml', 0.6307851076126099, 'gis', 2), ('earthlab/earthpy', 0.5730497241020203, 'gis', 2), ('perrygeo/python-rasterstats', 0.5707691311836243, 'gis', 0), ('microsoft/torchgeo', 0.5599908828735352, 'gis', 1), ('osgeo/grass', 0.5594460368156433, 'gis', 3), ('corteva/rioxarray', 0.5278557538986206, 'gis', 1), ('cogeotiff/rio-tiler', 0.5156446099281311, 'gis', 1), ('residentmario/geoplot', 0.5153622627258301, 'gis', 1)] | 562 | 6 | null | 70.27 | 578 | 506 | 137 | 0 | 11 | 15 | 11 | 578 | 1,053 | 90 | 1.8 | 60 |
978 | sim | https://github.com/astropy/astropy | [] | null | [] | [] | null | null | null | astropy/astropy | astropy | 4,079 | 1,687 | 139 | Python | https://www.astropy.org | Astronomy and astrophysics core library | astropy | 2024-01-14 | 2011-07-21 | 653 | 6.239729 | https://avatars.githubusercontent.com/u/847984?v=4 | Astronomy and astrophysics core library | ['astronomy', 'astrophysics', 'astropy', 'science'] | ['astronomy', 'astrophysics', 'astropy', 'science'] | 2024-01-13 | [('roban/cosmolopy', 0.5209611654281616, 'sim', 1)] | 514 | 7 | null | 37.42 | 561 | 395 | 152 | 0 | 9 | 12 | 9 | 561 | 2,172 | 90 | 3.9 | 60 |
1,820 | ml | https://github.com/google-deepmind/graphcast | ['forecasting'] | GraphCast: Learning skillful medium-range global weather forecasting | [] | [] | null | null | null | google-deepmind/graphcast | graphcast | 3,312 | 358 | 56 | Python | null | null | google-deepmind | 2024-01-14 | 2023-07-14 | 28 | 115.92 | https://avatars.githubusercontent.com/u/8596759?v=4 | GraphCast: Learning skillful medium-range global weather forecasting | ['weather', 'weather-forecast'] | ['forecasting', 'weather', 'weather-forecast'] | 2024-01-05 | [] | 8 | 2 | null | 0.29 | 45 | 17 | 6 | 0 | 1 | 2 | 1 | 45 | 125 | 90 | 2.8 | 60 |
1,879 | data | https://github.com/avaiga/taipy | [] | null | [] | [] | null | null | null | avaiga/taipy | taipy | 2,952 | 237 | 30 | Python | https://www.taipy.io | Turns Data and AI algorithms into production-ready web applications in no time. | avaiga | 2024-01-14 | 2022-02-18 | 101 | 29.063291 | https://avatars.githubusercontent.com/u/86434771?v=4 | Turns Data and AI algorithms into production-ready web applications in no time. | ['automation', 'data-engineering', 'data-ops', 'data-visualization', 'datascience', 'developer-tools', 'hacktoberfest2023', 'mlops', 'orchestration', 'pipeline', 'pipelines', 'taipy-core', 'taipy-gui', 'workflow'] | ['automation', 'data-engineering', 'data-ops', 'data-visualization', 'datascience', 'developer-tools', 'hacktoberfest2023', 'mlops', 'orchestration', 'pipeline', 'pipelines', 'taipy-core', 'taipy-gui', 'workflow'] | 2024-01-14 | [('bentoml/bentoml', 0.6463702321052551, 'ml-ops', 1), ('netflix/metaflow', 0.6367209553718567, 'ml-ops', 2), ('ploomber/ploomber', 0.6359885334968567, 'ml-ops', 4), ('mage-ai/mage-ai', 0.6288012266159058, 'ml-ops', 4), ('dagster-io/dagster', 0.6245914101600647, 'ml-ops', 4), ('orchest/orchest', 0.6196687817573547, 'ml-ops', 1), ('ml-tooling/opyrator', 0.617566704750061, 'viz', 0), ('kestra-io/kestra', 0.6105530858039856, 'ml-ops', 4), ('lastmile-ai/aiconfig', 0.6097587943077087, 'util', 1), ('meltano/meltano', 0.608718752861023, 'ml-ops', 2), ('polyaxon/polyaxon', 0.6045488119125366, 'ml-ops', 3), ('sweepai/sweep', 0.6026955842971802, 'llm', 1), ('flyteorg/flyte', 0.6026946902275085, 'ml-ops', 2), ('zenml-io/zenml', 0.5993794202804565, 'ml-ops', 3), ('pythagora-io/gpt-pilot', 0.5966109037399292, 'llm', 1), ('cheshire-cat-ai/core', 0.5955442786216736, 'llm', 0), ('prefecthq/server', 0.5884959697723389, 'util', 3), ('dagworks-inc/hamilton', 0.5867727994918823, 'ml-ops', 3), ('polyaxon/datatile', 0.5837622880935669, 'pandas', 2), ('superduperdb/superduperdb', 0.5622673034667969, 'data', 1), ('pathwaycom/llm-app', 0.5616130232810974, 'llm', 0), ('fmind/mlops-python-package', 0.5603728890419006, 'template', 1), ('pydoit/doit', 0.5572507977485657, 'util', 1), ('allegroai/clearml', 0.5540127158164978, 'ml-ops', 1), ('mindsdb/mindsdb', 0.5504463315010071, 'data', 0), ('airbytehq/airbyte', 0.5423561334609985, 'data', 2), ('prefecthq/marvin', 0.5397293567657471, 'nlp', 0), ('apache/airflow', 0.5394763946533203, 'ml-ops', 5), ('mlc-ai/mlc-llm', 0.5353958010673523, 'llm', 0), ('microsoft/promptflow', 0.5334009528160095, 'llm', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5292978286743164, 'template', 0), ('merantix-momentum/squirrel-core', 0.5268411636352539, 'ml', 0), ('alirezadir/machine-learning-interview-enlightener', 0.5267717242240906, 'study', 0), ('microsoft/lmops', 0.5267688632011414, 'llm', 0), ('googlecloudplatform/vertex-ai-samples', 0.5246182680130005, 'ml', 1), ('huggingface/datasets', 0.5236226916313171, 'nlp', 0), ('hi-primus/optimus', 0.5233602523803711, 'ml-ops', 0), ('iterative/dvc', 0.5210314989089966, 'ml-ops', 1), ('featureform/embeddinghub', 0.5199906229972839, 'nlp', 1), ('drivendata/cookiecutter-data-science', 0.519536018371582, 'template', 0), ('chaostoolkit/chaostoolkit', 0.5186023712158203, 'util', 1), ('feast-dev/feast', 0.5180974006652832, 'ml-ops', 2), ('wandb/client', 0.5176960825920105, 'ml', 1), ('bodywork-ml/bodywork-core', 0.5173805952072144, 'ml-ops', 3), ('reloadware/reloadium', 0.5162569284439087, 'profiling', 0), ('streamlit/streamlit', 0.5149668455123901, 'viz', 2), ('whylabs/whylogs', 0.5133393406867981, 'util', 1), ('fugue-project/fugue', 0.5130361318588257, 'pandas', 0), ('antonosika/gpt-engineer', 0.5112882852554321, 'llm', 0), ('hpcaitech/colossalai', 0.5108974575996399, 'llm', 0), ('mlflow/mlflow', 0.5100282430648804, 'ml-ops', 0), ('plotly/dash', 0.5096752047538757, 'viz', 1), ('tox-dev/tox', 0.5081842541694641, 'testing', 1), ('activeloopai/deeplake', 0.5062883496284485, 'ml-ops', 1), ('explosion/thinc', 0.5057910680770874, 'ml-dl', 0), ('backtick-se/cowait', 0.5056573152542114, 'util', 1), ('willmcgugan/textual', 0.5015890002250671, 'term', 0)] | 46 | 3 | null | 37.62 | 382 | 214 | 23 | 0 | 12 | 8 | 12 | 382 | 366 | 90 | 1 | 60 |
434 | nlp | https://github.com/argilla-io/argilla | [] | null | [] | [] | null | null | null | argilla-io/argilla | argilla | 2,823 | 284 | 24 | Python | https://docs.argilla.io | ✨Argilla: the open-source feedback platform for LLMs | argilla-io | 2024-01-14 | 2021-04-28 | 143 | 19.623635 | https://avatars.githubusercontent.com/u/18415507?v=4 | ✨Argilla: the open-source feedback platform for LLMs | ['active-learning', 'ai', 'annotation-tool', 'developer-tools', 'gpt-4', 'human-in-the-loop', 'langchain', 'llm', 'machine-learning', 'mlops', 'natural-language-processing', 'nlp', 'rlhf', 'text-annotation', 'text-labeling', 'weak-supervision', 'weakly-supervised-learning'] | ['active-learning', 'ai', 'annotation-tool', 'developer-tools', 'gpt-4', 'human-in-the-loop', 'langchain', 'llm', 'machine-learning', 'mlops', 'natural-language-processing', 'nlp', 'rlhf', 'text-annotation', 'text-labeling', 'weak-supervision', 'weakly-supervised-learning'] | 2024-01-12 | [('explosion/spacy-llm', 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1,469 | llm | https://github.com/alpha-vllm/llama2-accessory | ['pre-training', 'fine-tuning', 'deployment'] | null | [] | [] | null | null | null | alpha-vllm/llama2-accessory | LLaMA2-Accessory | 2,054 | 129 | 30 | Python | https://llama2-accessory.readthedocs.io/ | An Open-source Toolkit for LLM Development | alpha-vllm | 2024-01-13 | 2023-07-21 | 27 | 74.497409 | https://avatars.githubusercontent.com/u/140153551?v=4 | An Open-source Toolkit for LLM Development | [] | ['deployment', 'fine-tuning', 'pre-training'] | 2024-01-11 | [('tigerlab-ai/tiger', 0.7141748666763306, 'llm', 1), ('h2oai/h2o-llmstudio', 0.6861495971679688, 'llm', 1), ('bentoml/openllm', 0.6482536792755127, 'ml-ops', 1), ('iryna-kondr/scikit-llm', 0.6441587209701538, 'llm', 0), ('hegelai/prompttools', 0.6420565247535706, 'llm', 0), ('agenta-ai/agenta', 0.6384699940681458, 'llm', 0), ('ray-project/llm-applications', 0.6254207491874695, 'llm', 1), ('microsoft/promptflow', 0.6248592734336853, 'llm', 0), ('salesforce/codet5', 0.6213086843490601, 'nlp', 0), ('microsoft/semantic-kernel', 0.6138186454772949, 'llm', 0), ('lightning-ai/lit-gpt', 0.6060934066772461, 'llm', 1), ('argilla-io/argilla', 0.6045132875442505, 'nlp', 0), ('microsoft/torchscale', 0.602177619934082, 'llm', 0), ('eugeneyan/open-llms', 0.6008363962173462, 'study', 0), ('salesforce/xgen', 0.5997952222824097, 'llm', 0), ('citadel-ai/langcheck', 0.5963909029960632, 'llm', 0), ('pathwaycom/llm-app', 0.5948898196220398, 'llm', 0), ('young-geng/easylm', 0.5873928070068359, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5765708088874817, 'study', 0), ('bigscience-workshop/petals', 0.5728069543838501, 'data', 0), ('nat/openplayground', 0.5689014792442322, 'llm', 0), ('vllm-project/vllm', 0.5688649415969849, 'llm', 0), ('deepset-ai/haystack', 0.5652121305465698, 'llm', 0), ('run-llama/llama-hub', 0.561208963394165, 'data', 0), ('hiyouga/llama-factory', 0.5589560270309448, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5589559078216553, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5544970035552979, 'perf', 0), ('microsoft/jarvis', 0.5535730719566345, 'llm', 0), ('ajndkr/lanarky', 0.552966833114624, 'llm', 0), ('nomic-ai/gpt4all', 0.5511795878410339, 'llm', 0), ('conceptofmind/toolformer', 0.5475521087646484, 'llm', 0), ('night-chen/toolqa', 0.542137086391449, 'llm', 0), ('numba/llvmlite', 0.539250910282135, 'util', 0), ('hwchase17/langchain', 0.5383664965629578, 'llm', 0), ('confident-ai/deepeval', 0.5373701453208923, 'testing', 0), ('ludwig-ai/ludwig', 0.5365805625915527, 'ml-ops', 1), ('langchain-ai/langsmith-cookbook', 0.5349544286727905, 'llm', 0), ('shishirpatil/gorilla', 0.5339228510856628, 'llm', 0), ('nebuly-ai/nebullvm', 0.5258677005767822, 'perf', 0), ('openbmb/toolbench', 0.5172504186630249, 'llm', 0), ('alphasecio/langchain-examples', 0.5159311890602112, 'llm', 0), ('berriai/litellm', 0.5151165127754211, 'llm', 0), ('truera/trulens', 0.5145223140716553, 'llm', 0), ('deep-diver/pingpong', 0.5120090842247009, 'llm', 0), ('openai/evals', 0.5116733312606812, 'llm', 0), ('run-llama/llama-lab', 0.5041949152946472, 'llm', 0), ('salesforce/jaxformer', 0.5040596723556519, 'llm', 0), ('cg123/mergekit', 0.5024479627609253, 'llm', 0), ('zenml-io/zenml', 0.5014763474464417, 'ml-ops', 0), ('mmabrouk/chatgpt-wrapper', 0.5011169910430908, 'llm', 0)] | 19 | 5 | null | 9.48 | 73 | 61 | 6 | 0 | 0 | 0 | 0 | 73 | 107 | 90 | 1.5 | 60 |
1,709 | llm | https://github.com/huggingface/text-embeddings-inference | [] | null | [] | [] | null | null | null | huggingface/text-embeddings-inference | text-embeddings-inference | 1,520 | 65 | 20 | Rust | https://huggingface.co/docs/text-embeddings-inference/quick_tour | A blazing fast inference solution for text embeddings models | huggingface | 2024-01-14 | 2023-10-13 | 15 | 97.614679 | https://avatars.githubusercontent.com/u/25720743?v=4 | A blazing fast inference solution for text embeddings models | ['ai', 'embeddings', 'huggingface', 'llm', 'ml'] | ['ai', 'embeddings', 'huggingface', 'llm', 'ml'] | 2024-01-04 | [('chroma-core/chroma', 0.5832590460777283, 'data', 1), ('plasticityai/magnitude', 0.5618109703063965, 'nlp', 1), ('amansrivastava17/embedding-as-service', 0.5573744177818298, 'nlp', 2), ('koaning/whatlies', 0.5444438457489014, 'nlp', 1), ('infinitylogesh/mutate', 0.531061053276062, 'nlp', 0), ('sebischair/lbl2vec', 0.5274394154548645, 'nlp', 0), ('facebookresearch/pytorch-biggraph', 0.5272315144538879, 'ml-dl', 0), ('hpcaitech/energonai', 0.5272306799888611, 'ml', 0), ('google-research/electra', 0.5215802788734436, 'ml-dl', 0), ('llmware-ai/llmware', 0.517711341381073, 'llm', 2), ('huggingface/text-generation-inference', 0.5171723365783691, 'llm', 0), ('koaning/embetter', 0.5125843286514282, 'data', 0), ('jina-ai/clip-as-service', 0.5006672143936157, 'nlp', 0)] | 7 | 2 | null | 1.25 | 110 | 87 | 3 | 0 | 8 | 32 | 8 | 110 | 172 | 90 | 1.6 | 60 |
1,591 | testing | https://github.com/confident-ai/deepeval | ['language-model', 'unit-testing'] | null | [] | [] | null | null | null | confident-ai/deepeval | deepeval | 1,014 | 60 | 9 | Python | https://docs.confident-ai.com/ | The Evaluation Framework for LLMs | confident-ai | 2024-01-13 | 2023-08-10 | 24 | 41.028902 | https://avatars.githubusercontent.com/u/130858411?v=4 | The Evaluation Framework for LLMs | ['chatgpt', 'evaluate-models', 'evaluate-news-article-with-nlp', 'evaluation', 'evaluation-framework', 'evaluation-metrics', 'large', 'llm', 'llm-evaluation', 'llm-evaluation-framework', 'llmops'] | ['chatgpt', 'evaluate-models', 'evaluate-news-article-with-nlp', 'evaluation', 'evaluation-framework', 'evaluation-metrics', 'language-model', 'large', 'llm', 'llm-evaluation', 'llm-evaluation-framework', 'llmops', 'unit-testing'] | 2024-01-12 | [('agenta-ai/agenta', 0.690017819404602, 'llm', 3), ('openai/evals', 0.6733431816101074, 'llm', 3), ('citadel-ai/langcheck', 0.6523064374923706, 'llm', 2), ('hiyouga/llama-factory', 0.6391016840934753, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.6391015648841858, 'llm', 2), ('mooler0410/llmspracticalguide', 0.6305698156356812, 'study', 0), ('ai21labs/lm-evaluation', 0.622775137424469, 'llm', 2), ('eugeneyan/open-llms', 0.6072402596473694, 'study', 1), ('young-geng/easylm', 0.6033726334571838, 'llm', 1), ('deepset-ai/haystack', 0.5944290161132812, 'llm', 2), ('explosion/spacy-llm', 0.5939695239067078, 'llm', 1), ('dylanhogg/llmgraph', 0.581521213054657, 'ml', 2), ('microsoft/torchscale', 0.581218957901001, 'llm', 0), ('llmware-ai/llmware', 0.5799471735954285, 'llm', 0), ('bentoml/openllm', 0.575341522693634, 'ml-ops', 2), ('h2oai/h2o-llmstudio', 0.5734099745750427, 'llm', 2), ('lianjiatech/belle', 0.5731056332588196, 'llm', 0), ('argilla-io/argilla', 0.5710536241531372, 'nlp', 1), ('giskard-ai/giskard', 0.5690423250198364, 'data', 1), ('microsoft/promptflow', 0.5659092664718628, 'llm', 2), ('lm-sys/fastchat', 0.5658591985702515, 'llm', 2), ('hegelai/prompttools', 0.5625259876251221, 'llm', 0), ('paddlepaddle/paddlenlp', 0.556614100933075, 'llm', 1), ('fasteval/fasteval', 0.5521769523620605, 'llm', 2), ('hwchase17/langchain', 0.5516130328178406, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5511168241500854, 'perf', 0), ('pathwaycom/llm-app', 0.549860417842865, 'llm', 2), ('jerryjliu/llama_index', 0.5483352541923523, 'llm', 2), ('microsoft/autogen', 0.5460978746414185, 'llm', 2), ('arize-ai/phoenix', 0.5458160042762756, 'ml-interpretability', 1), ('nomic-ai/gpt4all', 0.5438401699066162, 'llm', 1), ('salesforce/xgen', 0.5417569875717163, 'llm', 2), ('next-gpt/next-gpt', 0.5388375520706177, 'llm', 2), ('alpha-vllm/llama2-accessory', 0.5373701453208923, 'llm', 0), ('thudm/chatglm2-6b', 0.5323322415351868, 'llm', 1), ('microsoft/promptcraft-robotics', 0.5318647623062134, 'sim', 2), ('deep-diver/pingpong', 0.5305920243263245, 'llm', 0), ('night-chen/toolqa', 0.529060959815979, 'llm', 0), ('tigerlab-ai/tiger', 0.5287721157073975, 'llm', 1), ('nebuly-ai/nebullvm', 0.5270206928253174, 'perf', 1), ('ibm/dromedary', 0.5251967906951904, 'llm', 1), ('langchain-ai/langsmith-cookbook', 0.5237811803817749, 'llm', 2), ('anthropics/evals', 0.5211471915245056, 'llm', 0), ('salesforce/codet5', 0.5176749229431152, 'nlp', 1), ('bobazooba/xllm', 0.5172545909881592, 'llm', 2), ('truera/trulens', 0.5170626640319824, 'llm', 3), ('rlancemartin/auto-evaluator', 0.5153782963752747, 'llm', 1), ('shishirpatil/gorilla', 0.5115599036216736, 'llm', 2), ('zilliztech/gptcache', 0.5101267099380493, 'llm', 2), ('juncongmoo/pyllama', 0.5091282725334167, 'llm', 0), ('openbmb/toolbench', 0.5041009783744812, 'llm', 1), ('guidance-ai/guidance', 0.5033418536186218, 'llm', 2), ('eth-sri/lmql', 0.5033408403396606, 'llm', 2), ('bigscience-workshop/petals', 0.5002102255821228, 'data', 0)] | 14 | 3 | null | 26.6 | 202 | 182 | 5 | 0 | 24 | 124 | 24 | 202 | 335 | 90 | 1.7 | 60 |
1,344 | util | https://github.com/faif/python-patterns | [] | null | [] | [] | null | null | null | faif/python-patterns | python-patterns | 38,820 | 6,988 | 1,661 | Python | null | A collection of design patterns/idioms in Python | faif | 2024-01-14 | 2012-06-06 | 607 | 63.86369 | null | A collection of design patterns/idioms in Python | ['design-patterns', 'idioms'] | ['design-patterns', 'idioms'] | 2023-01-27 | [('brandon-rhodes/python-patterns', 0.6763890385627747, 'util', 0), ('cosmicpython/book', 0.532017707824707, 'study', 0), ('grahamdumpleton/wrapt', 0.5319310426712036, 'util', 0), ('xrudelis/pytrait', 0.516368567943573, 'util', 0), ('pytoolz/toolz', 0.5127255320549011, 'util', 0)] | 128 | 4 | null | 0 | 2 | 2 | 141 | 12 | 0 | 0 | 0 | 2 | 11 | 90 | 5.5 | 59 |
108 | sim | https://github.com/atsushisakai/pythonrobotics | [] | null | [] | [] | null | null | null | atsushisakai/pythonrobotics | PythonRobotics | 20,781 | 6,275 | 511 | Python | https://atsushisakai.github.io/PythonRobotics/ | Python sample codes for robotics algorithms. | atsushisakai | 2024-01-14 | 2016-03-21 | 410 | 50.667712 | null | Python sample codes for robotics algorithms. | ['algorithm', 'animation', 'autonomous-driving', 'autonomous-navigation', 'autonomous-vehicles', 'control', 'cvxpy', 'ekf', 'localization', 'mapping', 'path-planning', 'robot', 'robotics', 'slam'] | ['algorithm', 'animation', 'autonomous-driving', 'autonomous-navigation', 'autonomous-vehicles', 'control', 'cvxpy', 'ekf', 'localization', 'mapping', 'path-planning', 'robot', 'robotics', 'slam'] | 2024-01-09 | [('thealgorithms/python', 0.58967125415802, 'study', 1), ('scikit-mobility/scikit-mobility', 0.5399863719940186, 'gis', 0), ('keon/algorithms', 0.5353425741195679, 'util', 1), ('python-odin/odin', 0.5244603753089905, 'util', 0), ('pandas-dev/pandas', 0.5196974277496338, 'pandas', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5075343251228333, 'study', 0)] | 121 | 4 | null | 2.56 | 59 | 56 | 95 | 0 | 0 | 0 | 0 | 59 | 27 | 90 | 0.5 | 59 |
2 | ml-dl | https://github.com/apache/incubator-mxnet | [] | null | [] | [] | null | null | null | apache/incubator-mxnet | mxnet | 20,667 | 6,894 | 1,074 | C++ | https://mxnet.apache.org | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more | apache | 2024-01-14 | 2015-04-30 | 456 | 45.251486 | https://avatars.githubusercontent.com/u/47359?v=4 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more | ['mxnet'] | ['mxnet'] | 2023-01-26 | [('microsoft/deepspeed', 0.6390171051025391, 'ml-dl', 0), ('horovod/horovod', 0.6248153448104858, 'ml-ops', 1), ('nvidia/deeplearningexamples', 0.5984542965888977, 'ml-dl', 1), ('paddlepaddle/paddle', 0.5943779349327087, 'ml-dl', 0), ('alpa-projects/alpa', 0.5928085446357727, 'ml-dl', 0), ('google/trax', 0.583592414855957, 'ml-dl', 0), ('microsoft/onnxruntime', 0.5671101212501526, 'ml', 0), ('aiqc/aiqc', 0.560641884803772, 'ml-ops', 0), ('tensorflow/tensorflow', 0.5543745160102844, 'ml-dl', 0), ('determined-ai/determined', 0.5505608320236206, 'ml-ops', 0), ('neuralmagic/deepsparse', 0.53566974401474, 'nlp', 0), ('tensorflow/tensor2tensor', 0.5354474186897278, 'ml', 0), ('ray-project/ray', 0.5308846235275269, 'ml-ops', 0), ('bigscience-workshop/petals', 0.5274662971496582, 'data', 0), ('salesforce/warp-drive', 0.5272499322891235, 'ml-rl', 0), ('uber/petastorm', 0.5250005722045898, 'data', 0), ('deepmind/dm-haiku', 0.522907018661499, 'ml-dl', 0), ('denys88/rl_games', 0.5211288332939148, 'ml-rl', 0), ('keras-team/keras', 0.5203127861022949, 'ml-dl', 0), ('deepmind/dm_control', 0.5190567374229431, 'ml-rl', 0), ('adap/flower', 0.5179499387741089, 'ml-ops', 0), ('tensorlayer/tensorlayer', 0.5166865587234497, 'ml-rl', 0), ('huggingface/transformers', 0.5165125131607056, 'nlp', 0), ('ashleve/lightning-hydra-template', 0.5147703886032104, 'util', 0), ('explosion/thinc', 0.5136386156082153, 'ml-dl', 1), ('tlkh/tf-metal-experiments', 0.5093386769294739, 'perf', 0), ('microsoft/jarvis', 0.5016826391220093, 'llm', 0), ('merantix-momentum/squirrel-core', 0.500947892665863, 'ml', 0)] | 983 | 8 | null | 0.02 | 6 | 0 | 106 | 12 | 0 | 5 | 5 | 6 | 10 | 90 | 1.7 | 59 |
19 | time-series | https://github.com/facebook/prophet | ['time-series'] | null | [] | [] | 1 | null | null | facebook/prophet | prophet | 17,356 | 4,467 | 423 | Python | https://facebook.github.io/prophet | Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. | facebook | 2024-01-13 | 2016-11-16 | 375 | 46.177119 | https://avatars.githubusercontent.com/u/69631?v=4 | Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. | ['forecasting', 'r'] | ['forecasting', 'r', 'time-series'] | 2023-10-18 | [('nixtla/statsforecast', 0.586733341217041, 'time-series', 2), ('alkaline-ml/pmdarima', 0.581493079662323, 'time-series', 2), ('linkedin/greykite', 0.5375127196311951, 'ml', 0), ('winedarksea/autots', 0.5207078456878662, 'time-series', 2), ('firmai/atspy', 0.5104213356971741, 'time-series', 2)] | 173 | 4 | null | 0.65 | 58 | 16 | 87 | 3 | 4 | 2 | 4 | 58 | 72 | 90 | 1.2 | 59 |
177 | debug | https://github.com/cool-rr/pysnooper | [] | null | [] | [] | 1 | null | null | cool-rr/pysnooper | PySnooper | 16,144 | 954 | 232 | Python | null | Never use print for debugging again | cool-rr | 2024-01-14 | 2019-04-18 | 249 | 64.649886 | null | Never use print for debugging again | ['debug', 'debugger', 'introspection', 'logging'] | ['debug', 'debugger', 'introspection', 'logging'] | 2024-01-13 | [('gruns/icecream', 0.8130260705947876, 'debug', 1), ('samuelcolvin/python-devtools', 0.5116415619850159, 'debug', 1)] | 27 | 5 | null | 0.19 | 4 | 1 | 58 | 0 | 1 | 4 | 1 | 4 | 8 | 90 | 2 | 59 |
56 | term | https://github.com/pallets/click | ['terminal'] | null | [] | [] | 1 | null | null | pallets/click | click | 14,685 | 1,418 | 183 | Python | https://click.palletsprojects.com | Python composable command line interface toolkit | pallets | 2024-01-14 | 2014-04-24 | 509 | 28.810258 | https://avatars.githubusercontent.com/u/16748505?v=4 | Python composable command line interface toolkit | ['cli', 'click', 'pallets'] | ['cli', 'click', 'pallets', 'terminal'] | 2023-12-29 | [('google/python-fire', 0.6196329593658447, 'term', 1), ('pexpect/pexpect', 0.5701817870140076, 'util', 0), ('jquast/blessed', 0.5604668855667114, 'term', 2), ('hoffstadt/dearpygui', 0.5539004802703857, 'gui', 0), ('textualize/trogon', 0.5391209125518799, 'term', 3), ('beeware/toga', 0.5282005667686462, 'gui', 0), ('urwid/urwid', 0.5238144993782043, 'term', 0), ('python-poetry/cleo', 0.5077859163284302, 'term', 1)] | 366 | 3 | null | 1.87 | 43 | 27 | 118 | 0 | 4 | 5 | 4 | 43 | 53 | 90 | 1.2 | 59 |
1,215 | gamedev | https://github.com/kitao/pyxel | [] | null | [] | [] | null | null | null | kitao/pyxel | pyxel | 12,839 | 842 | 228 | Python | null | A retro game engine for Python | kitao | 2024-01-14 | 2018-06-10 | 294 | 43.62767 | null | A retro game engine for Python | ['8bit', 'fantasy-console', 'game', 'game-development', 'game-engine', 'gamedev', 'gameengine', 'pico-8', 'pyxel', 'rust', 'tic-80'] | ['8bit', 'fantasy-console', 'game', 'game-development', 'game-engine', 'gamedev', 'gameengine', 'pico-8', 'pyxel', 'rust', 'tic-80'] | 2024-01-13 | [('pokepetter/ursina', 0.6735712885856628, 'gamedev', 2), ('panda3d/panda3d', 0.6634293794631958, 'gamedev', 3), ('lordmauve/pgzero', 0.6230867505073547, 'gamedev', 0), ('renpy/renpy', 0.5945414304733276, 'viz', 1), ('pygame/pygame', 0.5883877873420715, 'gamedev', 2), ('pythonarcade/arcade', 0.5633159875869751, 'gamedev', 0), ('pygamelib/pygamelib', 0.5561051964759827, 'gamedev', 2), ('prefecthq/marvin', 0.520916759967804, 'nlp', 0), ('quantconnect/lean', 0.5179747343063354, 'finance', 0), ('willmcgugan/textual', 0.5071513056755066, 'term', 0)] | 60 | 0 | null | 9.88 | 36 | 29 | 68 | 0 | 14 | 13 | 14 | 36 | 90 | 90 | 2.5 | 59 |
61 | pandas | https://github.com/ydataai/ydata-profiling | [] | null | [] | [] | 1 | null | null | ydataai/ydata-profiling | ydata-profiling | 11,667 | 1,607 | 150 | Python | https://docs.profiling.ydata.ai | 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames. | ydataai | 2024-01-14 | 2016-01-09 | 420 | 27.750255 | https://avatars.githubusercontent.com/u/57689451?v=4 | 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames. | ['big-data-analytics', 'data-analysis', 'data-exploration', 'data-profiling', 'data-quality', 'data-science', 'deep-learning', 'eda', 'exploration', 'exploratory-data-analysis', 'html-report', 'jupyter', 'jupyter-notebook', 'machine-learning', 'pandas', 'pandas-dataframe', 'pandas-profiling', 'statistics'] | ['big-data-analytics', 'data-analysis', 'data-exploration', 'data-profiling', 'data-quality', 'data-science', 'deep-learning', 'eda', 'exploration', 'exploratory-data-analysis', 'html-report', 'jupyter', 'jupyter-notebook', 'machine-learning', 'pandas', 'pandas-dataframe', 'pandas-profiling', 'statistics'] | 2024-01-08 | [('ydataai/ydata-quality', 0.6654260754585266, 'data', 2), ('hi-primus/optimus', 0.6320505142211914, 'ml-ops', 5), ('polyaxon/datatile', 0.6102992296218872, 'pandas', 6), ('great-expectations/great_expectations', 0.606023907661438, 'ml-ops', 5), ('unionai-oss/pandera', 0.5934801697731018, 'pandas', 2), ('pandas-dev/pandas', 0.5782955884933472, 'pandas', 3), ('apache/spark', 0.546349048614502, 'data', 0), ('lux-org/lux', 0.542782723903656, 'viz', 4), ('pola-rs/polars', 0.5423642992973328, 'pandas', 0), ('dagworks-inc/hamilton', 0.5421671867370605, 'ml-ops', 4), ('man-group/dtale', 0.5416145324707031, 'viz', 4), ('modin-project/modin', 0.5375041365623474, 'perf', 2), ('rapidsai/cudf', 0.5349627733230591, 'pandas', 3), ('krzjoa/awesome-python-data-science', 0.5310283303260803, 'study', 5), ('gventuri/pandas-ai', 0.5286967158317566, 'pandas', 3), ('plotly/dash', 0.526740312576294, 'viz', 2), ('ranaroussi/quantstats', 0.5242244005203247, 'finance', 0), ('rubik/radon', 0.5186936259269714, 'util', 0), ('eventual-inc/daft', 0.5120884776115417, 'pandas', 3), ('mementum/bta-lib', 0.5118176937103271, 'finance', 0)] | 117 | 3 | null | 2.83 | 80 | 30 | 98 | 0 | 17 | 38 | 17 | 80 | 92 | 90 | 1.1 | 59 |
50 | viz | https://github.com/mwaskom/seaborn | [] | null | [] | [] | null | null | null | mwaskom/seaborn | seaborn | 11,575 | 1,870 | 259 | Python | https://seaborn.pydata.org | Statistical data visualization in Python | mwaskom | 2024-01-14 | 2012-06-18 | 606 | 19.096158 | null | Statistical data visualization in Python | ['data-science', 'data-visualization', 'matplotlib', 'pandas'] | ['data-science', 'data-visualization', 'matplotlib', 'pandas'] | 2024-01-13 | [('altair-viz/altair', 0.8215170502662659, 'viz', 0), ('enthought/mayavi', 0.7422676086425781, 'viz', 0), ('man-group/dtale', 0.73142409324646, 'viz', 3), ('residentmario/geoplot', 0.7261803150177002, 'gis', 1), ('matplotlib/matplotlib', 0.6802253127098083, 'viz', 3), ('kanaries/pygwalker', 0.6736312508583069, 'pandas', 2), ('lux-org/lux', 0.6733652949333191, 'viz', 2), ('scitools/iris', 0.6527572870254517, 'gis', 0), ('jakevdp/pythondatasciencehandbook', 0.6520794630050659, 'study', 2), ('holoviz/panel', 0.6487950086593628, 'viz', 1), ('pyqtgraph/pyqtgraph', 0.6456829905509949, 'viz', 0), ('holoviz/holoviz', 0.6366784572601318, 'viz', 0), ('holoviz/hvplot', 0.636111855506897, 'pandas', 0), ('bokeh/bokeh', 0.6307612061500549, 'viz', 0), ('contextlab/hypertools', 0.6260726451873779, 'ml', 1), ('cuemacro/chartpy', 0.6233909130096436, 'viz', 1), ('has2k1/plotnine', 0.6059504747390747, 'viz', 0), ('matplotlib/mplfinance', 0.6046485900878906, 'finance', 1), ('pandas-dev/pandas', 0.6021502017974854, 'pandas', 2), ('holoviz/geoviews', 0.5874853134155273, 'gis', 0), ('scitools/cartopy', 0.5874788761138916, 'gis', 1), ('dfki-ric/pytransform3d', 0.5858793258666992, 'math', 1), ('datapane/datapane', 0.5832452774047852, 'viz', 1), ('adamerose/pandasgui', 0.5795894861221313, 'pandas', 1), ('plotly/plotly.py', 0.5750998854637146, 'viz', 0), ('gregorhd/mapcompare', 0.573523998260498, 'gis', 0), ('blaze/blaze', 0.5715226531028748, 'pandas', 0), ('tkrabel/bamboolib', 0.5646217465400696, 'pandas', 1), ('wesm/pydata-book', 0.5627793073654175, 'study', 0), ('csurfer/pyheat', 0.5626926422119141, 'profiling', 1), ('geopandas/geopandas', 0.5595967769622803, 'gis', 1), ('alexmojaki/heartrate', 0.5591291785240173, 'debug', 0), ('eleutherai/pyfra', 0.5522692799568176, 'ml', 0), ('westhealth/pyvis', 0.5389178395271301, 'graph', 0), ('mckinsey/vizro', 0.535768449306488, 'viz', 1), ('marcomusy/vedo', 0.5347036123275757, 'viz', 0), ('plotly/dash', 0.5341764092445374, 'viz', 2), ('vizzuhq/ipyvizzu', 0.5341234803199768, 'jupyter', 1), ('raphaelquast/eomaps', 0.531478226184845, 'gis', 1), ('federicoceratto/dashing', 0.528854489326477, 'term', 0), ('artelys/geonetworkx', 0.5267704129219055, 'gis', 0), ('netflix/flamescope', 0.5240253806114197, 'viz', 1), ('rjt1990/pyflux', 0.522447407245636, 'time-series', 0), ('graphistry/pygraphistry', 0.5153336524963379, 'data', 1), ('scikit-learn/scikit-learn', 0.5135470628738403, 'ml', 1), ('holoviz/holoviews', 0.513229489326477, 'viz', 0), ('stan-dev/pystan', 0.5127715468406677, 'ml', 0), ('mito-ds/monorepo', 0.5123574733734131, 'jupyter', 3), ('rapidsai/cudf', 0.5099605917930603, 'pandas', 2), ('holoviz/spatialpandas', 0.5058495402336121, 'pandas', 1), ('earthlab/earthpy', 0.5044101476669312, 'gis', 0), ('pysal/pysal', 0.5034690499305725, 'gis', 0), ('hazyresearch/meerkat', 0.5017697215080261, 'viz', 2), ('giswqs/geemap', 0.5008442401885986, 'gis', 1), ('matplotlib/basemap', 0.500274658203125, 'gis', 0), ('polyaxon/datatile', 0.500043511390686, 'pandas', 4)] | 210 | 5 | null | 2.29 | 127 | 92 | 141 | 0 | 3 | 3 | 3 | 127 | 285 | 90 | 2.2 | 59 |
1,375 | ml | https://github.com/deepmind/alphafold | ['protein', 'biology'] | Implementation of the inference pipeline of AlphaFold v2 | [] | [] | null | null | null | deepmind/alphafold | alphafold | 11,231 | 2,018 | 215 | Python | null | Open source code for AlphaFold. | deepmind | 2024-01-14 | 2021-06-17 | 136 | 82.149425 | https://avatars.githubusercontent.com/u/8596759?v=4 | Open source code for AlphaFold. | [] | ['biology', 'protein'] | 2023-11-01 | [] | 19 | 3 | null | 0.54 | 82 | 30 | 31 | 2 | 1 | 5 | 1 | 82 | 154 | 90 | 1.9 | 59 |
1,782 | util | https://github.com/caronc/apprise | [] | null | [] | [] | null | null | null | caronc/apprise | apprise | 9,247 | 335 | 61 | Python | https://hub.docker.com/r/caronc/apprise | Apprise - Push Notifications that work with just about every platform! | caronc | 2024-01-14 | 2017-11-25 | 322 | 28.67922 | null | Apprise - Push Notifications that work with just about every platform! | ['alerts', 'apprise', 'framework', 'notification-api', 'notification-hub', 'notification-service', 'notifications', 'notifier', 'notify', 'push-notifications'] | ['alerts', 'apprise', 'framework', 'notification-api', 'notification-hub', 'notification-service', 'notifications', 'notifier', 'notify', 'push-notifications'] | 2024-01-06 | [('liiight/notifiers', 0.6810635924339294, 'util', 3)] | 57 | 3 | null | 2.21 | 81 | 55 | 75 | 0 | 7 | 8 | 7 | 81 | 179 | 90 | 2.2 | 59 |
1,391 | finance | https://github.com/ai4finance-foundation/finrl | ['reinforcement-learning'] | null | [] | [] | null | null | null | ai4finance-foundation/finrl | FinRL | 8,598 | 2,131 | 194 | Jupyter Notebook | https://discord.gg/trsr8SXpW5 | FinRL: Financial Reinforcement Learning. 🔥 | ai4finance-foundation | 2024-01-13 | 2020-07-26 | 183 | 46.910366 | https://avatars.githubusercontent.com/u/68813910?v=4 | FinRL: Financial Reinforcement Learning. 🔥 | ['algorithmic-trading', 'deep-reinforcement-learning', 'drl-algorithms', 'drl-framework', 'drl-trading-agents', 'finance', 'fintech', 'multi-agent-learning', 'openai-gym', 'pythorch', 'stock-markets', 'stock-trading', 'tensorflow2', 'trading-tasks'] | ['algorithmic-trading', 'deep-reinforcement-learning', 'drl-algorithms', 'drl-framework', 'drl-trading-agents', 'finance', 'fintech', 'multi-agent-learning', 'openai-gym', 'pythorch', 'reinforcement-learning', 'stock-markets', 'stock-trading', 'tensorflow2', 'trading-tasks'] | 2024-01-14 | [('ai4finance-foundation/fingpt', 0.6304659247398376, 'finance', 3), ('polakowo/vectorbt', 0.6179881691932678, 'finance', 2), ('keras-rl/keras-rl', 0.5993512272834778, 'ml-rl', 1), ('pytorch/rl', 0.5981391072273254, 'ml-rl', 1), ('openbb-finance/openbbterminal', 0.5771132111549377, 'finance', 1), ('thu-ml/tianshou', 0.5749337673187256, 'ml-rl', 0), ('chancefocus/pixiu', 0.5721709132194519, 'finance', 1), ('tensorlayer/tensorlayer', 0.5661175847053528, 'ml-rl', 1), ('google/dopamine', 0.5640981793403625, 'ml-rl', 0), ('google/trax', 0.5627601146697998, 'ml-dl', 2), ('denys88/rl_games', 0.5618516206741333, 'ml-rl', 1), ('microsoft/qlib', 0.5603201389312744, 'finance', 3), ('quantconnect/lean', 0.5530506372451782, 'finance', 1), ('adap/flower', 0.551112949848175, 'ml-ops', 0), ('explosion/thinc', 0.5454742312431335, 'ml-dl', 0), ('google/tf-quant-finance', 0.54345703125, 'finance', 1), ('nccr-itmo/fedot', 0.5424655675888062, 'ml-ops', 0), ('opentensor/bittensor', 0.5417373776435852, 'ml', 0), ('zvtvz/zvt', 0.5343793034553528, 'finance', 2), ('kernc/backtesting.py', 0.5252265334129333, 'finance', 2), ('salesforce/warp-drive', 0.5230139493942261, 'ml-rl', 1), ('facebookresearch/reagent', 0.5226213932037354, 'ml-rl', 0), ('unity-technologies/ml-agents', 0.5189048647880554, 'ml-rl', 2), ('pettingzoo-team/pettingzoo', 0.5186222791671753, 'ml-rl', 1), ('freqtrade/freqtrade', 0.5126928091049194, 'crypto', 1), ('ddbourgin/numpy-ml', 0.511791467666626, 'ml', 1), ('xplainable/xplainable', 0.5115347504615784, 'ml-interpretability', 0), ('idanya/algo-trader', 0.5114476084709167, 'finance', 1), ('online-ml/river', 0.5111426711082458, 'ml', 0), ('nevronai/metisfl', 0.5089988112449646, 'ml', 0), ('ranaroussi/quantstats', 0.5057669878005981, 'finance', 2), ('keras-team/keras', 0.5041005611419678, 'ml-dl', 0), ('deepmind/dm_control', 0.5040066838264465, 'ml-rl', 1), ('farama-foundation/gymnasium', 0.5031803250312805, 'ml-rl', 1), ('tensorly/tensorly', 0.5015732645988464, 'ml-dl', 0)] | 108 | 4 | null | 4.33 | 51 | 17 | 42 | 0 | 1 | 1 | 1 | 51 | 53 | 90 | 1 | 59 |
151 | ml | https://github.com/catboost/catboost | [] | null | [] | [] | null | null | null | catboost/catboost | catboost | 7,539 | 1,164 | 197 | Python | https://catboost.ai | A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. | catboost | 2024-01-14 | 2017-07-18 | 341 | 22.108504 | https://avatars.githubusercontent.com/u/29043415?v=4 | A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. | ['big-data', 'catboost', 'categorical-features', 'coreml', 'cuda', 'data-mining', 'data-science', 'decision-trees', 'gbdt', 'gbm', 'gpu', 'gpu-computing', 'gradient-boosting', 'kaggle', 'machine-learning', 'r', 'tutorial'] | ['big-data', 'catboost', 'categorical-features', 'coreml', 'cuda', 'data-mining', 'data-science', 'decision-trees', 'gbdt', 'gbm', 'gpu', 'gpu-computing', 'gradient-boosting', 'kaggle', 'machine-learning', 'r', 'tutorial'] | 2024-01-13 | [('microsoft/lightgbm', 0.8396483659744263, 'ml', 8), ('dmlc/xgboost', 0.7875171899795532, 'ml', 3), ('google/tf-quant-finance', 0.5715440511703491, 'finance', 2), ('gradio-app/gradio', 0.553999125957489, 'viz', 2), ('pycaret/pycaret', 0.5486772656440735, 'ml', 3), ('dask/dask-ml', 0.5368636250495911, 'ml', 0), ('oml-team/open-metric-learning', 0.5297994017601013, 'ml', 1), ('rasbt/mlxtend', 0.5251424908638, 'ml', 3), ('determined-ai/determined', 0.5235607028007507, 'ml-ops', 2), ('intel/intel-extension-for-pytorch', 0.5203407406806946, 'perf', 1), ('linkedin/fasttreeshap', 0.5170351266860962, 'ml', 1), ('epistasislab/tpot', 0.515169084072113, 'ml', 3), ('microsoft/flaml', 0.5135185122489929, 'ml', 2), ('rasbt/machine-learning-book', 0.5105630159378052, 'study', 1), ('tensorflow/tensorflow', 0.5088467597961426, 'ml-dl', 1), ('tensorflow/data-validation', 0.5083582997322083, 'ml-ops', 0), ('teamhg-memex/eli5', 0.5058757066726685, 'ml', 2), ('pytorch/torchrec', 0.5050163269042969, 'ml-dl', 2), ('scikit-learn-contrib/lightning', 0.5035675764083862, 'ml', 1), ('uber/petastorm', 0.5008516311645508, 'data', 1)] | 1,193 | 2 | null | 28.46 | 217 | 46 | 79 | 0 | 3 | 14 | 3 | 217 | 167 | 90 | 0.8 | 59 |
783 | diffusion | https://github.com/ashawkey/stable-dreamfusion | [] | null | [] | [] | null | null | null | ashawkey/stable-dreamfusion | stable-dreamfusion | 7,424 | 672 | 125 | Python | null | Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion. | ashawkey | 2024-01-14 | 2022-10-06 | 68 | 108.04158 | null | Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion. | ['dreamfusion', 'gui', 'image-to-3d', 'nerf', 'stable-diffusion', 'text-to-3d'] | ['dreamfusion', 'gui', 'image-to-3d', 'nerf', 'stable-diffusion', 'text-to-3d'] | 2023-08-02 | [('carson-katri/dream-textures', 0.5740616917610168, 'diffusion', 1), ('xavierxiao/dreambooth-stable-diffusion', 0.5586757659912109, 'diffusion', 1), ('sharonzhou/long_stable_diffusion', 0.5333707332611084, 'diffusion', 0), ('openai/point-e', 0.5210638642311096, 'util', 0), ('automatic1111/stable-diffusion-webui', 0.5163194537162781, 'diffusion', 1), ('huggingface/exporters', 0.503178060054779, 'ml', 0), ('thereforegames/unprompted', 0.5019211769104004, 'diffusion', 1)] | 20 | 7 | null | 1.75 | 14 | 5 | 16 | 6 | 2 | 2 | 2 | 13 | 11 | 90 | 0.8 | 59 |
355 | ml-ops | https://github.com/netflix/metaflow | [] | null | [] | [] | null | null | null | netflix/metaflow | metaflow | 7,269 | 703 | 275 | Python | https://metaflow.org | :rocket: Build and manage real-life data science projects with ease! | netflix | 2024-01-14 | 2019-09-17 | 228 | 31.881579 | https://avatars.githubusercontent.com/u/913567?v=4 | 🚀 Build and manage real-life data science projects with ease! | ['ai', 'aws', 'azure', 'data-science', 'datascience', 'gcp', 'high-performance-computing', 'kubernetes', 'machine-learning', 'ml', 'ml-infrastructure', 'ml-platform', 'mlops', 'model-management', 'productivity', 'r', 'r-package', 'reproducible-research', 'rstats'] | ['ai', 'aws', 'azure', 'data-science', 'datascience', 'gcp', 'high-performance-computing', 'kubernetes', 'machine-learning', 'ml', 'ml-infrastructure', 'ml-platform', 'mlops', 'model-management', 'productivity', 'r', 'r-package', 'reproducible-research', 'rstats'] | 2024-01-11 | [('polyaxon/polyaxon', 0.6915358901023865, 'ml-ops', 5), ('iterative/dvc', 0.6912345886230469, 'ml-ops', 3), ('bentoml/bentoml', 0.6758896708488464, 'ml-ops', 6), ('orchest/orchest', 0.6532567739486694, 'ml-ops', 3), ('feast-dev/feast', 0.6503940224647522, 'ml-ops', 4), ('mlflow/mlflow', 0.6375054717063904, 'ml-ops', 4), ('avaiga/taipy', 0.6367209553718567, 'data', 2), ('ploomber/ploomber', 0.6208223700523376, 'ml-ops', 3), ('googlecloudplatform/vertex-ai-samples', 0.6179714798927307, 'ml', 5), ('skypilot-org/skypilot', 0.6102747321128845, 'llm', 4), ('flyteorg/flyte', 0.608452320098877, 'ml-ops', 4), ('dagster-io/dagster', 0.6058613657951355, 'ml-ops', 2), ('kubeflow/pipelines', 0.5999767184257507, 'ml-ops', 4), ('mage-ai/mage-ai', 0.5949897766113281, 'ml-ops', 2), ('aimhubio/aim', 0.5948770046234131, 'ml-ops', 5), ('mindsdb/mindsdb', 0.594740092754364, 'data', 3), ('polyaxon/datatile', 0.5876936316490173, 'pandas', 2), ('allegroai/clearml', 0.5861303210258484, 'ml-ops', 3), ('bodywork-ml/bodywork-core', 0.5834348201751709, 'ml-ops', 4), ('airbytehq/airbyte', 0.5793136954307556, 'data', 0), ('zenml-io/mlstacks', 0.5789435505867004, 'ml-ops', 2), ('zenml-io/zenml', 0.5758110880851746, 'ml-ops', 5), ('jina-ai/jina', 0.5668376088142395, 'ml', 3), ('whylabs/whylogs', 0.5658851861953735, 'util', 3), ('fmind/mlops-python-package', 0.5633413195610046, 'template', 3), ('meltano/meltano', 0.5626580119132996, 'ml-ops', 0), ('merantix-momentum/squirrel-core', 0.560415506362915, 'ml', 4), ('activeloopai/deeplake', 0.5537254214286804, 'ml-ops', 5), ('cleanlab/cleanlab', 0.5494846105575562, 'ml', 1), ('alirezadir/machine-learning-interview-enlightener', 0.5488802194595337, 'study', 2), ('xplainable/xplainable', 0.5485888123512268, 'ml-interpretability', 2), ('featureform/embeddinghub', 0.5473335981369019, 'nlp', 4), ('hpcaitech/colossalai', 0.5460145473480225, 'llm', 1), ('drivendata/cookiecutter-data-science', 0.5439575910568237, 'template', 3), ('superduperdb/superduperdb', 0.542826235294342, 'data', 3), ('pythagora-io/gpt-pilot', 0.5420463681221008, 'llm', 1), ('kubeflow-kale/kale', 0.5416892170906067, 'ml-ops', 1), ('lastmile-ai/aiconfig', 0.5414328575134277, 'util', 1), ('eventual-inc/daft', 0.5369682312011719, 'pandas', 2), ('huggingface/datasets', 0.5358194708824158, 'nlp', 1), ('sweepai/sweep', 0.5298407077789307, 'llm', 1), ('hi-primus/optimus', 0.5270899534225464, 'ml-ops', 2), ('kestra-io/kestra', 0.5250420570373535, 'ml-ops', 0), ('streamlit/streamlit', 0.5236718654632568, 'viz', 2), ('dagworks-inc/hamilton', 0.519896924495697, 'ml-ops', 3), ('lithops-cloud/lithops', 0.5198798179626465, 'ml-ops', 1), ('antonosika/gpt-engineer', 0.5169954299926758, 'llm', 1), ('zenodo/zenodo', 0.513927161693573, 'util', 0), ('google/ml-metadata', 0.5132206082344055, 'ml-ops', 0), ('transformeroptimus/superagi', 0.5128297209739685, 'llm', 1), ('pydoit/doit', 0.5121597051620483, 'util', 1), ('wandb/client', 0.5120764374732971, 'ml', 4), ('airbnb/knowledge-repo', 0.5116251707077026, 'data', 1), ('salesforce/logai', 0.5108799934387207, 'util', 2), ('unionai-oss/unionml', 0.5082710981369019, 'ml-ops', 2), ('google-research/language', 0.5073051452636719, 'nlp', 1), ('firmai/industry-machine-learning', 0.5058495402336121, 'study', 3), ('backtick-se/cowait', 0.5032603144645691, 'util', 2)] | 78 | 3 | null | 4.12 | 136 | 79 | 53 | 0 | 36 | 27 | 36 | 136 | 131 | 90 | 1 | 59 |
1,605 | term | https://github.com/saulpw/visidata | [] | null | [] | [] | null | null | null | saulpw/visidata | visidata | 7,159 | 271 | 70 | Python | http://visidata.org | A terminal spreadsheet multitool for discovering and arranging data | saulpw | 2024-01-14 | 2016-10-27 | 378 | 18.903433 | null | A terminal spreadsheet multitool for discovering and arranging data | ['cli', 'csv', 'datajournalism', 'datawrangling', 'devops-tools', 'eda', 'hdf5', 'json', 'opendata', 'pandas', 'reconciliation', 'spreadsheet', 'sqlite', 'tabular-data', 'tsv', 'tui', 'unix-toolkit'] | ['cli', 'csv', 'datajournalism', 'datawrangling', 'devops-tools', 'eda', 'hdf5', 'json', 'opendata', 'pandas', 'reconciliation', 'spreadsheet', 'sqlite', 'tabular-data', 'tsv', 'tui', 'unix-toolkit'] | 2024-01-14 | [('gristlabs/grist-core', 0.6072668433189392, 'data', 1), ('simonw/datasette', 0.6051476001739502, 'data', 3), ('hi-primus/optimus', 0.5910075902938843, 'ml-ops', 0), ('hyperqueryhq/whale', 0.5835681557655334, 'data', 0), ('wireservice/csvkit', 0.5774484276771545, 'util', 0), ('mito-ds/monorepo', 0.5757395625114441, 'jupyter', 1), ('jazzband/tablib', 0.5593103170394897, 'data', 0), ('holoviz/panel', 0.5565743446350098, 'viz', 0), ('python-odin/odin', 0.5557106137275696, 'util', 2), ('airbnb/omniduct', 0.5526487231254578, 'data', 0), ('pytables/pytables', 0.5493369102478027, 'data', 0), ('pandas-dev/pandas', 0.5462385416030884, 'pandas', 1), ('airbytehq/airbyte', 0.5434727668762207, 'data', 0), ('plotly/dash', 0.5414975881576538, 'viz', 0), ('airbnb/knowledge-repo', 0.5398018956184387, 'data', 0), ('unstructured-io/unstructured-api', 0.536859393119812, 'data', 0), ('koaning/clumper', 0.5350844264030457, 'util', 0), ('linealabs/lineapy', 0.5347519516944885, 'jupyter', 0), ('krzjoa/awesome-python-data-science', 0.5329089760780334, 'study', 0), ('tconbeer/harlequin', 0.5237422585487366, 'term', 0), ('dbt-labs/dbt-core', 0.5234029293060303, 'ml-ops', 0), ('intake/intake', 0.5221759080886841, 'data', 0), ('ibis-project/ibis', 0.5209618210792542, 'data', 2), ('zenodo/zenodo', 0.5197573900222778, 'util', 0), ('mckinsey/vizro', 0.517253577709198, 'viz', 0), ('man-group/dtale', 0.5157226324081421, 'viz', 1), ('dagster-io/dagster', 0.515415370464325, 'ml-ops', 0), ('tiangolo/sqlmodel', 0.513899564743042, 'data', 1), ('astanin/python-tabulate', 0.5104148387908936, 'util', 0), ('polyaxon/datatile', 0.5101152658462524, 'pandas', 1), ('ploomber/ploomber', 0.5074170827865601, 'ml-ops', 0), ('quantopian/qgrid', 0.5062557458877563, 'jupyter', 0), ('vaexio/vaex', 0.5060981512069702, 'perf', 2), ('malloydata/malloy-py', 0.5046626925468445, 'data', 0), ('unionai-oss/pandera', 0.5012566447257996, 'pandas', 1), ('apache/spark', 0.5010607838630676, 'data', 0), ('dagworks-inc/hamilton', 0.5007401704788208, 'ml-ops', 1), ('dlt-hub/dlt', 0.5002819299697876, 'data', 0)] | 96 | 3 | null | 21.27 | 269 | 213 | 88 | 0 | 4 | 8 | 4 | 269 | 516 | 90 | 1.9 | 59 |
287 | testing | https://github.com/hypothesisworks/hypothesis | [] | null | [] | [] | 1 | null | null | hypothesisworks/hypothesis | hypothesis | 7,097 | 590 | 72 | Python | https://hypothesis.works | Hypothesis is a powerful, flexible, and easy to use library for property-based testing. | hypothesisworks | 2024-01-13 | 2013-03-10 | 568 | 12.488436 | https://avatars.githubusercontent.com/u/18481919?v=4 | Hypothesis is a powerful, flexible, and easy to use library for property-based testing. | ['fuzzing', 'property-based-testing', 'testing'] | ['fuzzing', 'property-based-testing', 'testing'] | 2024-01-13 | [('unionai-oss/pandera', 0.5685426592826843, 'pandas', 1), ('nedbat/coveragepy', 0.5107763409614563, 'testing', 0), ('pytest-dev/pytest', 0.505795955657959, 'testing', 1)] | 322 | 4 | null | 18.79 | 83 | 69 | 132 | 0 | 26 | 131 | 26 | 84 | 177 | 90 | 2.1 | 59 |
1,197 | diffusion | https://github.com/facebookresearch/dinov2 | [] | null | [] | [] | null | null | null | facebookresearch/dinov2 | dinov2 | 7,024 | 545 | 93 | Jupyter Notebook | null | PyTorch code and models for the DINOv2 self-supervised learning method. | facebookresearch | 2024-01-14 | 2023-03-29 | 43 | 160.156352 | https://avatars.githubusercontent.com/u/16943930?v=4 | PyTorch code and models for the DINOv2 self-supervised learning method. | [] | [] | 2023-12-01 | [('lightly-ai/lightly', 0.5861289501190186, 'ml', 0), ('idea-research/groundingdino', 0.5680932402610779, 'diffusion', 0), ('skorch-dev/skorch', 0.5518595576286316, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.5447684526443481, 'study', 0), ('pytorch/ignite', 0.5208505988121033, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.5111134052276611, 'perf', 0)] | 6 | 1 | null | 0.63 | 140 | 62 | 10 | 1 | 0 | 0 | 0 | 140 | 246 | 90 | 1.8 | 59 |
872 | time-series | https://github.com/unit8co/darts | [] | null | [] | [] | null | null | null | unit8co/darts | darts | 6,872 | 766 | 60 | Python | https://unit8co.github.io/darts/ | A python library for user-friendly forecasting and anomaly detection on time series. | unit8co | 2024-01-13 | 2018-09-13 | 280 | 24.480407 | https://avatars.githubusercontent.com/u/39619745?v=4 | A python library for user-friendly forecasting and anomaly detection on time series. | ['anomaly-detection', 'data-science', 'deep-learning', 'forecasting', 'machine-learning', 'time-series'] | ['anomaly-detection', 'data-science', 'deep-learning', 'forecasting', 'machine-learning', 'time-series'] | 2024-01-13 | [('aistream-peelout/flow-forecast', 0.7890238165855408, 'time-series', 4), ('yzhao062/pyod', 0.7557379603385925, 'data', 4), ('tdameritrade/stumpy', 0.7482045888900757, 'time-series', 2), ('salesforce/merlion', 0.7470134496688843, 'time-series', 4), ('pycaret/pycaret', 0.7233750820159912, 'ml', 4), ('alkaline-ml/pmdarima', 0.7097618579864502, 'time-series', 3), ('awslabs/gluonts', 0.6495864987373352, 'time-series', 5), ('firmai/atspy', 0.6426480412483215, 'time-series', 2), ('rjt1990/pyflux', 0.5929312109947205, 'time-series', 1), ('linkedin/greykite', 0.5859647989273071, 'ml', 0), ('sktime/sktime', 0.5841982960700989, 'time-series', 4), ('salesforce/deeptime', 0.5719814300537109, 'time-series', 3), ('google/temporian', 0.5616124272346497, 'time-series', 1), ('opengeos/earthformer', 0.5380537509918213, 'gis', 2), ('rasbt/mlxtend', 0.5370567440986633, 'ml', 2), ('winedarksea/autots', 0.5341631770133972, 'time-series', 4), ('scikit-learn-contrib/imbalanced-learn', 0.5324269533157349, 'ml', 2), ('blue-yonder/tsfresh', 0.5309851765632629, 'time-series', 2), ('uber/orbit', 0.5234378576278687, 'time-series', 3), ('wilsonrljr/sysidentpy', 0.5214325785636902, 'time-series', 3), ('microprediction/microprediction', 0.5138264298439026, 'time-series', 1), ('salesforce/logai', 0.5133403539657593, 'util', 2)] | 110 | 4 | null | 3.79 | 228 | 127 | 65 | 0 | 5 | 7 | 5 | 228 | 353 | 90 | 1.5 | 59 |
1,090 | llm | https://github.com/eleutherai/gpt-neox | [] | null | [] | [] | null | null | null | eleutherai/gpt-neox | gpt-neox | 6,319 | 921 | 121 | Python | null | An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library. | eleutherai | 2024-01-13 | 2020-12-22 | 162 | 39.006173 | https://avatars.githubusercontent.com/u/68924597?v=4 | An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library. | ['deepspeed-library', 'gpt-3', 'language-model', 'transformers'] | ['deepspeed-library', 'gpt-3', 'language-model', 'transformers'] | 2024-01-13 | [('eleutherai/gpt-neo', 0.6265007257461548, 'llm', 3), ('microsoft/deepspeed', 0.5843392610549927, 'ml-dl', 0), ('marella/ctransformers', 0.5529630184173584, 'nlp', 1), ('karpathy/mingpt', 0.5511136651039124, 'llm', 0), ('huggingface/optimum', 0.5265071988105774, 'ml', 1), ('pytorch/pytorch', 0.5058263540267944, 'ml-dl', 0), ('nvidia/tensorrt-llm', 0.5021648406982422, 'viz', 1)] | 111 | 4 | null | 3.4 | 83 | 56 | 37 | 0 | 2 | 1 | 2 | 83 | 114 | 90 | 1.4 | 59 |
763 | data | https://github.com/gristlabs/grist-core | [] | null | [] | [] | null | null | null | gristlabs/grist-core | grist-core | 5,846 | 240 | 50 | TypeScript | https://www.getgrist.com/ | Grist is the evolution of spreadsheets. | gristlabs | 2024-01-14 | 2020-05-22 | 192 | 30.357567 | https://avatars.githubusercontent.com/u/19978005?v=4 | Grist is the evolution of spreadsheets. | ['awesome', 'database', 'spreadsheet'] | ['awesome', 'database', 'spreadsheet'] | 2024-01-11 | [('saulpw/visidata', 0.6072668433189392, 'term', 1)] | 73 | 1 | null | 15.33 | 194 | 96 | 44 | 0 | 14 | 7 | 14 | 194 | 316 | 90 | 1.6 | 59 |
432 | util | https://github.com/scikit-image/scikit-image | [] | null | [] | [] | null | null | null | scikit-image/scikit-image | scikit-image | 5,735 | 2,241 | 186 | Python | https://scikit-image.org | Image processing in Python | scikit-image | 2024-01-13 | 2011-07-07 | 655 | 8.746187 | https://avatars.githubusercontent.com/u/897180?v=4 | Image processing in Python | ['computer-vision', 'image-processing', 'spec-0', 'spec-1', 'spec-4'] | ['computer-vision', 'image-processing', 'spec-0', 'spec-1', 'spec-4'] | 2024-01-11 | [('luispedro/mahotas', 0.6524010300636292, 'viz', 1), ('python-pillow/pillow', 0.6156206130981445, 'util', 1), ('zulko/moviepy', 0.5875822305679321, 'util', 0), ('imageio/imageio', 0.5782924890518188, 'util', 0), ('networkx/networkx', 0.5438209772109985, 'graph', 3), ('lightly-ai/lightly', 0.5242587924003601, 'ml', 1), ('numpy/numpy', 0.5151585936546326, 'math', 0), ('roboflow/supervision', 0.5051987767219543, 'ml', 2)] | 644 | 8 | null | 10.75 | 209 | 99 | 152 | 0 | 11 | 9 | 11 | 208 | 481 | 90 | 2.3 | 59 |
1,258 | llm | https://github.com/lightning-ai/lit-llama | ['llama', 'language-model', 'nanogpt'] | null | [] | [] | null | null | null | lightning-ai/lit-llama | lit-llama | 5,520 | 473 | 67 | Python | null | Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. | lightning-ai | 2024-01-14 | 2023-03-22 | 44 | 123.057325 | https://avatars.githubusercontent.com/u/58386951?v=4 | Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. | [] | ['language-model', 'llama', 'nanogpt'] | 2023-07-19 | [('lightning-ai/lit-gpt', 0.721184253692627, 'llm', 1), ('jzhang38/tinyllama', 0.6785302758216858, 'llm', 2), ('microsoft/llama-2-onnx', 0.643981397151947, 'llm', 2), ('tloen/alpaca-lora', 0.6250495314598083, 'llm', 2), ('bobazooba/xllm', 0.6132877469062805, 'llm', 1), ('hiyouga/llama-factory', 0.5843560099601746, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5843559503555298, 'llm', 2), ('facebookresearch/llama', 0.5731508731842041, 'llm', 2), ('zrrskywalker/llama-adapter', 0.5725643038749695, 'llm', 2), ('bigscience-workshop/petals', 0.5701621770858765, 'data', 1), ('next-gpt/next-gpt', 0.5547515153884888, 'llm', 0), ('intel/intel-extension-for-transformers', 0.5519506335258484, 'perf', 0), ('run-llama/llama-lab', 0.550618588924408, 'llm', 2), ('facebookresearch/llama-recipes', 0.5484828352928162, 'llm', 2), ('young-geng/easylm', 0.5471640825271606, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.5464016199111938, 'llm', 0), ('facebookresearch/codellama', 0.5444297790527344, 'llm', 2), ('sjtu-ipads/powerinfer', 0.5379477143287659, 'llm', 1), ('oobabooga/text-generation-webui', 0.5357398986816406, 'llm', 1), ('jerryjliu/llama_index', 0.5328296422958374, 'llm', 2), ('opengvlab/omniquant', 0.5302090048789978, 'llm', 0), ('salesforce/xgen', 0.5283926129341125, 'llm', 1), ('cstankonrad/long_llama', 0.5269233584403992, 'llm', 2), ('haotian-liu/llava', 0.5264182686805725, 'llm', 1), ('lianjiatech/belle', 0.5208169221878052, 'llm', 1), ('openlm-research/open_llama', 0.5196517109870911, 'llm', 2), ('ggerganov/llama.cpp', 0.5175377726554871, 'llm', 2), ('vllm-project/vllm', 0.5155295729637146, 'llm', 1), ('artidoro/qlora', 0.5125903487205505, 'llm', 1), ('microsoft/lora', 0.5121870040893555, 'llm', 1), ('mlc-ai/web-llm', 0.508145809173584, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5055845975875854, 'llm', 1), ('paddlepaddle/paddlenlp', 0.5034503936767578, 'llm', 1), ('tairov/llama2.mojo', 0.501312792301178, 'llm', 1)] | 32 | 6 | null | 4.31 | 46 | 26 | 10 | 6 | 0 | 0 | 0 | 46 | 24 | 90 | 0.5 | 59 |
185 | ml-dl | https://github.com/google/flax | ['neural-network'] | null | [] | [] | null | null | null | google/flax | flax | 5,105 | 582 | 82 | Python | https://flax.readthedocs.io | Flax is a neural network library for JAX that is designed for flexibility. | google | 2024-01-14 | 2020-01-10 | 211 | 24.128967 | https://avatars.githubusercontent.com/u/1342004?v=4 | Flax is a neural network library for JAX that is designed for flexibility. | ['jax'] | ['jax', 'neural-network'] | 2024-01-12 | [('deepmind/dm-haiku', 0.6950955986976624, 'ml-dl', 1), ('deepmind/synjax', 0.6082916259765625, 'math', 1), ('deepmind/chex', 0.5962191820144653, 'ml-dl', 1), ('young-geng/easylm', 0.5341013073921204, 'llm', 1), ('google/trax', 0.5265333652496338, 'ml-dl', 1)] | 215 | 2 | null | 8.6 | 213 | 169 | 49 | 0 | 14 | 9 | 14 | 212 | 281 | 90 | 1.3 | 59 |
1,819 | study | https://github.com/udlbook/udlbook | ['book', 'deep-learning'] | null | [] | [] | null | null | null | udlbook/udlbook | udlbook | 4,087 | 847 | 76 | Jupyter Notebook | null | Understanding Deep Learning - Simon J.D. Prince | udlbook | 2024-01-14 | 2022-08-01 | 78 | 52.301645 | null | Understanding Deep Learning - Simon J.D. Prince | [] | ['book', 'deep-learning'] | 2024-01-10 | [('mrdbourke/pytorch-deep-learning', 0.6033921837806702, 'study', 1), ('rasbt/stat453-deep-learning-ss20', 0.5738182663917542, 'study', 0), ('d2l-ai/d2l-en', 0.573790431022644, 'study', 2), ('tensorflow/tensor2tensor', 0.5561156868934631, 'ml', 1), ('rasbt/deeplearning-models', 0.5459153056144714, 'ml-dl', 0), ('ageron/handson-ml2', 0.539566159248352, 'ml', 0), ('udacity/deep-learning-v2-pytorch', 0.5336586236953735, 'study', 1), ('openai/spinningup', 0.5261555314064026, 'study', 0), ('atcold/nyu-dlsp21', 0.5171167850494385, 'study', 1), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5133402347564697, 'study', 1), ('intellabs/bayesian-torch', 0.5086169838905334, 'ml', 1), ('patchy631/machine-learning', 0.5037120580673218, 'ml', 0), ('graykode/nlp-tutorial', 0.5029069185256958, 'study', 0), ('keras-team/keras', 0.5011566877365112, 'ml-dl', 1)] | 8 | 3 | null | 7.65 | 43 | 40 | 18 | 0 | 35 | 28 | 35 | 43 | 57 | 90 | 1.3 | 59 |
1,442 | llm | https://github.com/kyegomez/tree-of-thoughts | ['prompt-engineering'] | null | [] | [] | null | null | null | kyegomez/tree-of-thoughts | tree-of-thoughts | 3,761 | 361 | 48 | Python | https://discord.gg/qUtxnK2NMf | Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70% | kyegomez | 2024-01-14 | 2023-05-21 | 36 | 103.649606 | null | Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70% | ['artificial-intelligence', 'chatgpt', 'deep-learning', 'gpt4', 'multimodal', 'prompt', 'prompt-engineering', 'prompt-learning', 'prompt-tuning'] | ['artificial-intelligence', 'chatgpt', 'deep-learning', 'gpt4', 'multimodal', 'prompt', 'prompt-engineering', 'prompt-learning', 'prompt-tuning'] | 2023-12-24 | [('spcl/graph-of-thoughts', 0.6711254715919495, 'llm', 1), ('lupantech/chameleon-llm', 0.6684974431991577, 'llm', 1), ('keirp/automatic_prompt_engineer', 0.6476341485977173, 'llm', 1), ('eugeneyan/obsidian-copilot', 0.6086257100105286, 'llm', 0), ('stanfordnlp/dspy', 0.5961645245552063, 'llm', 0), ('guidance-ai/guidance', 0.5812641382217407, 'llm', 2), ('lupantech/scienceqa', 0.5537173748016357, 'llm', 0), ('srush/minichain', 0.5509519577026367, 'llm', 1), ('thudm/p-tuning-v2', 0.5489909052848816, 'nlp', 1), ('microsoft/autogen', 0.5404730439186096, 'llm', 1), ('reasoning-machines/pal', 0.5376133918762207, 'llm', 0), ('microsoft/generative-ai-for-beginners', 0.5277297496795654, 'study', 2), ('databrickslabs/dolly', 0.5184698104858398, 'llm', 0), ('openai/finetune-transformer-lm', 0.5154716968536377, 'llm', 0), ('promptslab/awesome-prompt-engineering', 0.5084075927734375, 'study', 6), ('jina-ai/thinkgpt', 0.5059940814971924, 'llm', 0), ('hazyresearch/ama_prompting', 0.5045536160469055, 'llm', 1)] | 7 | 3 | null | 4.6 | 7 | 2 | 8 | 1 | 30 | 46 | 30 | 7 | 7 | 90 | 1 | 59 |
4 | pandas | https://github.com/aws/aws-sdk-pandas | ['apache-arrow', 'parquet', 'awswrangler', 'emr'] | null | [] | [] | 1 | null | null | aws/aws-sdk-pandas | aws-sdk-pandas | 3,713 | 668 | 61 | Python | https://aws-sdk-pandas.readthedocs.io | pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). | aws | 2024-01-13 | 2019-02-26 | 257 | 14.447471 | https://avatars.githubusercontent.com/u/2232217?v=4 | pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). | ['amazon-athena', 'amazon-sagemaker-notebook', 'apache-arrow', 'apache-parquet', 'athena', 'aws', 'aws-glue', 'aws-lambda', 'data-engineering', 'data-science', 'emr', 'etl', 'glue-catalog', 'lambda', 'modin', 'mysql', 'pandas', 'ray', 'redshift'] | ['amazon-athena', 'amazon-sagemaker-notebook', 'apache-arrow', 'apache-parquet', 'athena', 'aws', 'aws-glue', 'aws-lambda', 'awswrangler', 'data-engineering', 'data-science', 'emr', 'etl', 'glue-catalog', 'lambda', 'modin', 'mysql', 'pandas', 'parquet', 'ray', 'redshift'] | 2024-01-12 | [('airbytehq/airbyte', 0.6343478560447693, 'data', 4), ('pynamodb/pynamodb', 0.6329684257507324, 'data', 1), ('prefecthq/prefect-aws', 0.6139408946037292, 'data', 1), ('airbnb/omniduct', 0.5810672044754028, 'data', 0), ('tobymao/sqlglot', 0.5701399445533752, 'data', 2), ('ibis-project/ibis', 0.563861608505249, 'data', 2), ('fugue-project/fugue', 0.5624109506607056, 'pandas', 1), ('awslabs/python-deequ', 0.5529321432113647, 'ml', 1), ('hi-primus/optimus', 0.533242404460907, 'ml-ops', 1), ('jordaneremieff/mangum', 0.5317604541778564, 'web', 3), ('zenodo/zenodo', 0.5311623811721802, 'util', 0), ('boto/boto3', 0.5303450226783752, 'util', 1), ('tiangolo/sqlmodel', 0.5277955532073975, 'data', 0), ('geeogi/async-python-lambda-template', 0.5274588465690613, 'template', 0), ('nficano/python-lambda', 0.5259411334991455, 'util', 2), ('astronomer/astro-sdk', 0.525879442691803, 'ml-ops', 3), ('simonw/datasette', 0.525142252445221, 'data', 0), ('apache/spark', 0.5226028561592102, 'data', 0), ('aws/chalice', 0.5215028524398804, 'web', 3), ('eventual-inc/daft', 0.5070556998252869, 'pandas', 2), ('amzn/ion-python', 0.5067648887634277, 'data', 0), ('pola-rs/polars', 0.50155109167099, 'pandas', 0), ('aws/graph-notebook', 0.5009594559669495, 'jupyter', 0)] | 143 | 4 | null | 7.15 | 140 | 127 | 59 | 0 | 14 | 24 | 14 | 140 | 498 | 90 | 3.6 | 59 |
1,496 | ml-ops | https://github.com/zenml-io/zenml | [] | null | [] | [] | null | null | null | zenml-io/zenml | zenml | 3,428 | 370 | 40 | Python | https://zenml.io | ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io. | zenml-io | 2024-01-14 | 2020-11-19 | 166 | 20.562125 | https://avatars.githubusercontent.com/u/88676955?v=4 | ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io. | ['ai', 'automl', 'data-science', 'deep-learning', 'devops-tools', 'llm', 'llmops', 'machine-learning', 'metadata-tracking', 'ml', 'mlops', 'pipelines', 'production-ready', 'pytorch', 'tensorflow', 'workflow', 'zenml'] | ['ai', 'automl', 'data-science', 'deep-learning', 'devops-tools', 'llm', 'llmops', 'machine-learning', 'metadata-tracking', 'ml', 'mlops', 'pipelines', 'production-ready', 'pytorch', 'tensorflow', 'workflow', 'zenml'] | 2024-01-13 | [('allegroai/clearml', 0.66759192943573, 'ml-ops', 4), ('polyaxon/polyaxon', 0.6621537804603577, 'ml-ops', 9), ('orchest/orchest', 0.6482174396514893, 'ml-ops', 3), ('ploomber/ploomber', 0.6197214722633362, 'ml-ops', 5), ('fmind/mlops-python-package', 0.6134677529335022, 'template', 3), ('avaiga/taipy', 0.5993794202804565, 'data', 3), ('bodywork-ml/bodywork-core', 0.5911761522293091, 'ml-ops', 3), ('getindata/kedro-kubeflow', 0.5848532915115356, 'ml-ops', 1), ('microsoft/nni', 0.5792359113693237, 'ml', 7), ('netflix/metaflow', 0.5758110880851746, 'ml-ops', 5), ('flyteorg/flyte', 0.5718936324119568, 'ml-ops', 5), ('bentoml/bentoml', 0.570486843585968, 'ml-ops', 5), ('apache/airflow', 0.5523534417152405, 'ml-ops', 4), ('zenml-io/mlstacks', 0.5486688613891602, 'ml-ops', 2), ('prefecthq/server', 0.5477404594421387, 'util', 1), ('lastmile-ai/aiconfig', 0.5441376566886902, 'util', 2), ('cheshire-cat-ai/core', 0.542861819267273, 'llm', 2), ('unionai-oss/unionml', 0.5419542193412781, 'ml-ops', 2), ('kestra-io/kestra', 0.5403246879577637, 'ml-ops', 1), ('jina-ai/jina', 0.5385584831237793, 'ml', 4), ('mage-ai/mage-ai', 0.5322885513305664, 'ml-ops', 3), ('tox-dev/tox', 0.5314726233482361, 'testing', 0), ('kubeflow/pipelines', 0.5281010866165161, 'ml-ops', 3), ('wandb/client', 0.5277370810508728, 'ml', 6), ('keras-team/autokeras', 0.5269325375556946, 'ml-dl', 4), ('selfexplainml/piml-toolbox', 0.5244457125663757, 'ml-interpretability', 0), ('mlflow/mlflow', 0.5241439938545227, 'ml-ops', 3), ('chaostoolkit/chaostoolkit', 0.5238291621208191, 'util', 1), ('ashleve/lightning-hydra-template', 0.5233268141746521, 'util', 3), ('meltano/meltano', 0.5218309760093689, 'ml-ops', 1), ('pythagora-io/gpt-pilot', 0.5131421089172363, 'llm', 1), ('titanml/takeoff', 0.5115346908569336, 'llm', 1), ('pathwaycom/llm-app', 0.504523515701294, 'llm', 3), ('whylabs/whylogs', 0.5043908357620239, 'util', 3), ('kedro-org/kedro', 0.5034431219100952, 'ml-ops', 2), ('determined-ai/determined', 0.5032854676246643, 'ml-ops', 6), ('alpha-vllm/llama2-accessory', 0.5014763474464417, 'llm', 0), ('ml-tooling/opyrator', 0.5011926293373108, 'viz', 1)] | 84 | 3 | null | 16.25 | 345 | 300 | 38 | 0 | 41 | 39 | 41 | 345 | 579 | 90 | 1.7 | 59 |
1,610 | llm | https://github.com/li-plus/chatglm.cpp | [] | null | [] | [] | null | null | null | li-plus/chatglm.cpp | chatglm.cpp | 2,154 | 330 | 32 | C++ | null | C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & more LLMs | li-plus | 2024-01-14 | 2023-05-23 | 36 | 59.833333 | null | C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & more LLMs | ['baichuan', 'baichuan2', 'chatglm', 'chatglm2', 'chatglm3', 'codegeex2-6b', 'internlm', 'large-language-models', 'nlp'] | ['baichuan', 'baichuan2', 'chatglm', 'chatglm2', 'chatglm3', 'codegeex2-6b', 'internlm', 'large-language-models', 'nlp'] | 2023-11-25 | [('thudm/chatglm2-6b', 0.7250033617019653, 'llm', 2), ('intel/intel-extension-for-transformers', 0.6037748456001282, 'perf', 0), ('microsoft/autogen', 0.5944321751594543, 'llm', 0), ('nomic-ai/gpt4all', 0.5896359086036682, 'llm', 0), ('next-gpt/next-gpt', 0.5851370096206665, 'llm', 1), ('hiyouga/llama-factory', 0.5838776230812073, 'llm', 3), ('hiyouga/llama-efficient-tuning', 0.5838775634765625, 'llm', 3), ('hwchase17/langchain', 0.5806834697723389, 'llm', 0), ('bobazooba/xllm', 0.5759797692298889, 'llm', 1), ('salesforce/xgen', 0.5746297240257263, 'llm', 2), ('fasteval/fasteval', 0.5682762265205383, 'llm', 0), ('eth-sri/lmql', 0.5538818836212158, 'llm', 0), ('embedchain/embedchain', 0.5471507906913757, 'llm', 0), ('baichuan-inc/baichuan-13b', 0.5446141362190247, 'llm', 1), ('mlc-ai/web-llm', 0.542007565498352, 'llm', 0), ('run-llama/rags', 0.5372152328491211, 'llm', 0), ('zilliztech/gptcache', 0.5297065377235413, 'llm', 0), ('dylanhogg/llmgraph', 0.524939239025116, 'ml', 0), ('artidoro/qlora', 0.5086432099342346, 'llm', 0), ('salesforce/codet5', 0.5017570853233337, 'nlp', 1)] | 11 | 6 | null | 1.37 | 122 | 48 | 8 | 2 | 12 | 18 | 12 | 122 | 223 | 90 | 1.8 | 59 |
1,423 | llm | https://github.com/hegelai/prompttools | ['prompt-engineering', 'testing'] | null | [] | [] | null | null | null | hegelai/prompttools | prompttools | 2,100 | 158 | 24 | Python | http://prompttools.readthedocs.io | Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB). | hegelai | 2024-01-14 | 2023-06-25 | 31 | 67.123288 | https://avatars.githubusercontent.com/u/136523567?v=4 | Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB). | ['deep-learning', 'developer-tools', 'embeddings', 'large-language-models', 'llms', 'machine-learning', 'prompt-engineering', 'vector-search'] | ['deep-learning', 'developer-tools', 'embeddings', 'large-language-models', 'llms', 'machine-learning', 'prompt-engineering', 'testing', 'vector-search'] | 2024-01-03 | [('agenta-ai/agenta', 0.6764405965805054, 'llm', 3), ('tigerlab-ai/tiger', 0.6615456342697144, 'llm', 1), ('argilla-io/argilla', 0.644296407699585, 'nlp', 2), ('alpha-vllm/llama2-accessory', 0.6420565247535706, 'llm', 0), ('doccano/doccano', 0.6014738082885742, 'nlp', 1), ('llmware-ai/llmware', 0.6007319092750549, 'llm', 3), ('eugeneyan/open-llms', 0.5875352621078491, 'study', 2), ('nomic-ai/gpt4all', 0.5853099226951599, 'llm', 0), ('lancedb/lancedb', 0.5837177634239197, 'data', 0), ('salesforce/codet5', 0.580586850643158, 'nlp', 1), ('night-chen/toolqa', 0.5785123109817505, 'llm', 1), ('nebuly-ai/nebullvm', 0.5767601132392883, 'perf', 1), ('promptslab/awesome-prompt-engineering', 0.5741844773292542, 'study', 3), ('microsoft/promptflow', 0.5713818669319153, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5667575001716614, 'study', 1), ('bentoml/openllm', 0.565089225769043, 'ml-ops', 0), ('young-geng/easylm', 0.5647485256195068, 'llm', 2), ('cheshire-cat-ai/core', 0.5646258592605591, 'llm', 1), ('confident-ai/deepeval', 0.5625259876251221, 'testing', 0), ('alphasecio/langchain-examples', 0.5608381628990173, 'llm', 0), ('conceptofmind/toolformer', 0.5603080987930298, 'llm', 0), ('bigscience-workshop/petals', 0.5545216202735901, 'data', 3), ('iryna-kondr/scikit-llm', 0.5520104765892029, 'llm', 2), ('deepset-ai/haystack', 0.5512160658836365, 'llm', 2), ('microsoft/lmops', 0.5492219924926758, 'llm', 0), ('salesforce/xgen', 0.5444273352622986, 'llm', 1), ('openbmb/toolbench', 0.5396706461906433, 'llm', 0), ('lm-sys/fastchat', 0.534296989440918, 'llm', 0), ('dylanhogg/llmgraph', 0.5341759324073792, 'ml', 0), ('pathwaycom/llm-app', 0.5340642333030701, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5304824709892273, 'llm', 0), ('neuml/txtai', 0.5288627743721008, 'nlp', 4), ('hiyouga/llama-efficient-tuning', 0.5267438292503357, 'llm', 2), ('hiyouga/llama-factory', 0.5267438292503357, 'llm', 2), ('bigscience-workshop/promptsource', 0.526086688041687, 'nlp', 1), ('microsoft/semantic-kernel', 0.5153470039367676, 'llm', 0), ('paddlepaddle/paddlenlp', 0.514409065246582, 'llm', 0), ('openai/evals', 0.513576090335846, 'llm', 0), ('embedchain/embedchain', 0.5133116245269775, 'llm', 0), ('wandb/client', 0.5127788186073303, 'ml', 2), ('microsoft/generative-ai-for-beginners', 0.5114457607269287, 'study', 2), ('ludwig-ai/ludwig', 0.5103862881660461, 'ml-ops', 2), ('microsoft/nni', 0.5096408128738403, 'ml', 2), ('citadel-ai/langcheck', 0.5087067484855652, 'llm', 0), ('activeloopai/deeplake', 0.5075566172599792, 'ml-ops', 4), ('shishirpatil/gorilla', 0.5024935603141785, 'llm', 0), ('bobazooba/xllm', 0.5022645592689514, 'llm', 2), ('mlflow/mlflow', 0.5002617239952087, 'ml-ops', 1)] | 10 | 3 | null | 11.04 | 28 | 15 | 7 | 0 | 5 | 10 | 5 | 28 | 41 | 90 | 1.5 | 59 |
1,741 | llm | https://github.com/cheshire-cat-ai/core | [] | null | [] | [] | null | null | null | cheshire-cat-ai/core | core | 1,490 | 186 | 19 | Python | https://cheshirecat.ai | Production ready AI assistant framework | cheshire-cat-ai | 2024-01-13 | 2023-02-08 | 50 | 29.297753 | https://avatars.githubusercontent.com/u/135242343?v=4 | Production ready AI assistant framework | ['ai', 'assistant', 'chatbot', 'docker', 'llm', 'plugin', 'vector-search'] | ['ai', 'assistant', 'chatbot', 'docker', 'llm', 'plugin', 'vector-search'] | 2024-01-04 | [('prefecthq/marvin', 0.7232251167297363, 'nlp', 2), ('embedchain/embedchain', 0.6973840594291687, 'llm', 2), ('pathwaycom/llm-app', 0.6957066059112549, 'llm', 2), ('deepset-ai/haystack', 0.6507551074028015, 'llm', 1), ('rcgai/simplyretrieve', 0.6481109261512756, 'llm', 0), ('lm-sys/fastchat', 0.6361826062202454, 'llm', 1), ('mindsdb/mindsdb', 0.6340122222900391, 'data', 3), ('microsoft/promptflow', 0.6264965534210205, 'llm', 2), ('rasahq/rasa', 0.6253566741943359, 'llm', 1), ('jina-ai/jina', 0.6241676807403564, 'ml', 1), ('microsoft/lmops', 0.6224048137664795, 'llm', 1), ('lastmile-ai/aiconfig', 0.6183017492294312, 'util', 2), ('sweepai/sweep', 0.6141369342803955, 'llm', 2), ('minimaxir/simpleaichat', 0.613688588142395, 'llm', 1), ('mlc-ai/mlc-llm', 0.6107067465782166, 'llm', 1), ('marqo-ai/marqo', 0.6071776151657104, 'ml', 1), ('llmware-ai/llmware', 0.6055431962013245, 'llm', 1), ('larsbaunwall/bricky', 0.598059892654419, 'llm', 1), ('bentoml/bentoml', 0.597477376461029, 'ml-ops', 1), ('nomic-ai/gpt4all', 0.5960567593574524, 'llm', 1), ('avaiga/taipy', 0.5955442786216736, 'data', 0), ('deeppavlov/deeppavlov', 0.5946456789970398, 'nlp', 2), ('microsoft/generative-ai-for-beginners', 0.594606339931488, 'study', 1), ('activeloopai/deeplake', 0.586743950843811, 'ml-ops', 3), ('togethercomputer/openchatkit', 0.5846368074417114, 'nlp', 1), ('chatarena/chatarena', 0.5810584425926208, 'llm', 1), ('antonosika/gpt-engineer', 0.5780220031738281, 'llm', 1), ('operand/agency', 0.5766038298606873, 'llm', 2), ('googlecloudplatform/vertex-ai-samples', 0.5718985199928284, 'ml', 1), ('run-llama/rags', 0.5686349868774414, 'llm', 2), ('nvidia/nemo', 0.5682287216186523, 'nlp', 0), ('hegelai/prompttools', 0.5646258592605591, 'llm', 1), ('krohling/bondai', 0.5621045827865601, 'llm', 0), ('lucidrains/toolformer-pytorch', 0.5618926882743835, 'llm', 0), ('microsoft/autogen', 0.5565327405929565, 'llm', 1), ('oegedijk/explainerdashboard', 0.5511989593505859, 'ml-interpretability', 0), ('thilinarajapakse/simpletransformers', 0.5490924715995789, 'nlp', 0), ('pytorchlightning/pytorch-lightning', 0.5489669442176819, 'ml-dl', 1), ('superduperdb/superduperdb', 0.547654926776886, 'data', 3), ('smol-ai/developer', 0.5464283227920532, 'llm', 1), ('h2oai/h2o-llmstudio', 0.5447829365730286, 'llm', 3), ('intel/intel-extension-for-transformers', 0.5444093346595764, 'perf', 1), ('microsoft/semantic-kernel', 0.5438644886016846, 'llm', 2), ('zenml-io/zenml', 0.542861819267273, 'ml-ops', 2), ('microsoft/chatgpt-robot-manipulation-prompts', 0.5411517024040222, 'llm', 0), ('hwchase17/langchain', 0.5408321619033813, 'llm', 1), ('fasteval/fasteval', 0.5404486060142517, 'llm', 1), ('alirezadir/machine-learning-interview-enlightener', 0.539746105670929, 'study', 1), ('argilla-io/argilla', 0.5388045907020569, 'nlp', 2), ('bigscience-workshop/petals', 0.5387936234474182, 'data', 1), ('transformeroptimus/superagi', 0.5372999310493469, 'llm', 2), ('lancedb/lancedb', 0.5356892347335815, 'data', 0), ('gunthercox/chatterbot', 0.53544682264328, 'nlp', 1), ('qdrant/qdrant', 0.5352751016616821, 'data', 1), ('nebuly-ai/nebullvm', 0.5341480374336243, 'perf', 2), ('ludwig-ai/ludwig', 0.5316358804702759, 'ml-ops', 1), ('tigerlab-ai/tiger', 0.5307193398475647, 'llm', 1), ('reloadware/reloadium', 0.5294227004051208, 'profiling', 1), ('kalliope-project/kalliope', 0.5292161107063293, 'util', 0), ('paddlepaddle/paddlenlp', 0.5240945219993591, 'llm', 1), ('killianlucas/open-interpreter', 0.5222368240356445, 'llm', 0), ('databrickslabs/dolly', 0.519527792930603, 'llm', 1), ('weaviate/verba', 0.5184066295623779, 'llm', 0), ('young-geng/easylm', 0.5178155899047852, 'llm', 1), ('fmind/mlops-python-package', 0.5158709287643433, 'template', 1), ('prefecthq/server', 0.5153402090072632, 'util', 0), ('polyaxon/datatile', 0.5147360563278198, 'pandas', 0), ('aimhubio/aim', 0.5146742463111877, 'ml-ops', 1), ('microsoft/promptcraft-robotics', 0.513721764087677, 'sim', 1), ('polyaxon/polyaxon', 0.512060284614563, 'ml-ops', 0), ('skypilot-org/skypilot', 0.510378360748291, 'llm', 0), ('microsoft/onnxruntime', 0.5098522901535034, 'ml', 0), ('facebookresearch/parlai', 0.5091173648834229, 'nlp', 0), ('huggingface/datasets', 0.508074939250946, 'nlp', 0), ('arize-ai/phoenix', 0.5057440400123596, 'ml-interpretability', 0), ('ml-tooling/opyrator', 0.5056010484695435, 'viz', 0), ('explosion/thinc', 0.5046352744102478, 'ml-dl', 1), ('mlflow/mlflow', 0.5041938424110413, 'ml-ops', 1), ('alphasecio/langchain-examples', 0.5036561489105225, 'llm', 1), ('eugeneyan/obsidian-copilot', 0.5033305287361145, 'llm', 2), ('pythagora-io/gpt-pilot', 0.5015438199043274, 'llm', 1)] | 59 | 2 | null | 23.79 | 206 | 186 | 11 | 0 | 0 | 20 | 20 | 205 | 370 | 90 | 1.8 | 59 |
1,851 | llm | https://github.com/epfllm/meditron | ['medical', 'language-model'] | null | [] | [] | null | null | null | epfllm/meditron | meditron | 1,291 | 131 | 20 | Python | https://huggingface.co/epfl-llm | Meditron is a suite of open-source medical Large Language Models (LLMs). | epfllm | 2024-01-13 | 2023-11-23 | 9 | 132.897059 | https://avatars.githubusercontent.com/u/129088087?v=4 | Meditron is a suite of open-source medical Large Language Models (LLMs). | [] | ['language-model', 'medical'] | 2024-01-12 | [('bigscience-workshop/biomedical', 0.5808714032173157, 'data', 0), ('qanastek/drbert', 0.5632989406585693, 'llm', 1), ('salesforce/xgen', 0.5559400320053101, 'llm', 1), ('tsinghuadatabasegroup/db-gpt', 0.5455986261367798, 'llm', 1), ('hannibal046/awesome-llm', 0.5448260307312012, 'study', 1), ('lianjiatech/belle', 0.5387333035469055, 'llm', 0), ('bobazooba/xllm', 0.5308298468589783, 'llm', 0), ('explosion/spacy-llm', 0.5306103825569153, 'llm', 0), ('kbressem/medalpaca', 0.5290087461471558, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5282127261161804, 'study', 0), ('eleutherai/the-pile', 0.5269107818603516, 'data', 0), ('young-geng/easylm', 0.5253199934959412, 'llm', 1), ('lm-sys/fastchat', 0.5228744149208069, 'llm', 1), ('eugeneyan/open-llms', 0.5213027596473694, 'study', 0), ('dylanhogg/llmgraph', 0.5147185921669006, 'ml', 0), ('juncongmoo/pyllama', 0.5138061046600342, 'llm', 0), ('agenta-ai/agenta', 0.5137256979942322, 'llm', 0), ('cg123/mergekit', 0.5135393738746643, 'llm', 0), ('next-gpt/next-gpt', 0.5075371265411377, 'llm', 0), ('ibm/dromedary', 0.5021689534187317, 'llm', 1), ('lucidrains/medical-chatgpt', 0.5020337104797363, 'llm', 0), ('tigerlab-ai/tiger', 0.501189649105072, 'llm', 0), ('ctlllll/llm-toolmaker', 0.5010691285133362, 'llm', 1)] | 9 | 6 | null | 1.15 | 25 | 17 | 2 | 0 | 0 | 0 | 0 | 25 | 33 | 90 | 1.3 | 59 |
164 | term | https://github.com/tqdm/tqdm | [] | null | [] | [] | 1 | null | null | tqdm/tqdm | tqdm | 26,830 | 1,377 | 207 | Python | https://tqdm.github.io | :zap: A Fast, Extensible Progress Bar for Python and CLI | tqdm | 2024-01-14 | 2015-06-03 | 451 | 59.377174 | https://avatars.githubusercontent.com/u/12731565?v=4 | :zap: A Fast, Extensible Progress Bar for Python and CLI | ['cli', 'console', 'discord', 'gui', 'jupyter', 'keras', 'meter', 'pandas', 'parallel', 'progress', 'progress-bar', 'progressbar', 'progressmeter', 'rate', 'telegram', 'terminal', 'time', 'utilities'] | ['cli', 'console', 'discord', 'gui', 'jupyter', 'keras', 'meter', 'pandas', 'parallel', 'progress', 'progress-bar', 'progressbar', 'progressmeter', 'rate', 'telegram', 'terminal', 'time', 'utilities'] | 2023-08-10 | [('wolph/python-progressbar', 0.7864949107170105, 'util', 9), ('rockhopper-technologies/enlighten', 0.7503482699394226, 'term', 0), ('rsalmei/alive-progress', 0.6888198256492615, 'util', 5), ('erotemic/ubelt', 0.5793629884719849, 'util', 1), ('sumerc/yappi', 0.549595832824707, 'profiling', 0), ('pypy/pypy', 0.5426979064941406, 'util', 0), ('hoffstadt/dearpygui', 0.5399507284164429, 'gui', 1), ('faster-cpython/ideas', 0.5260686874389648, 'perf', 0), ('pyqtgraph/pyqtgraph', 0.5137172341346741, 'viz', 0), ('faster-cpython/tools', 0.5104278922080994, 'perf', 0), ('ipython/ipyparallel', 0.5037369728088379, 'perf', 2), ('wxwidgets/phoenix', 0.5025215744972229, 'gui', 1)] | 112 | 3 | null | 0.6 | 51 | 6 | 105 | 5 | 5 | 18 | 5 | 51 | 46 | 90 | 0.9 | 58 |
31 | data | https://github.com/jaidedai/easyocr | [] | null | [] | [] | null | null | null | jaidedai/easyocr | EasyOCR | 20,722 | 2,893 | 299 | Python | https://www.jaided.ai | Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. | jaidedai | 2024-01-14 | 2020-03-14 | 202 | 102.366972 | https://avatars.githubusercontent.com/u/61448029?v=4 | Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. | ['cnn', 'crnn', 'data-mining', 'deep-learning', 'easyocr', 'image-processing', 'information-retrieval', 'lstm', 'machine-learning', 'ocr', 'optical-character-recognition', 'pytorch', 'scene-text', 'scene-text-recognition'] | ['cnn', 'crnn', 'data-mining', 'deep-learning', 'easyocr', 'image-processing', 'information-retrieval', 'lstm', 'machine-learning', 'ocr', 'optical-character-recognition', 'pytorch', 'scene-text', 'scene-text-recognition'] | 2023-09-04 | [('rapidai/rapidocr', 0.6983810663223267, 'data', 3), ('alibaba/easynlp', 0.5166882872581482, 'nlp', 3), ('lucidrains/imagen-pytorch', 0.5161765217781067, 'ml-dl', 1), ('madmaze/pytesseract', 0.5150726437568665, 'data', 1), ('hrnet/hrnet-semantic-segmentation', 0.5142496824264526, 'ml', 0), ('imageio/imageio', 0.5057637095451355, 'util', 0), ('huggingface/datasets', 0.5004381537437439, 'nlp', 3)] | 128 | 1 | null | 0.38 | 73 | 17 | 47 | 4 | 1 | 6 | 1 | 73 | 79 | 90 | 1.1 | 58 |
1,777 | ml-dl | https://github.com/openai/clip | ['clip'] | null | [] | [] | null | null | null | openai/clip | CLIP | 20,129 | 2,785 | 301 | Jupyter Notebook | null | CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image | openai | 2024-01-14 | 2020-12-16 | 162 | 123.599123 | https://avatars.githubusercontent.com/u/14957082?v=4 | CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image | ['deep-learning', 'machine-learning'] | ['clip', 'deep-learning', 'machine-learning'] | 2023-07-08 | [('jina-ai/clip-as-service', 0.6114118695259094, 'nlp', 1), ('rom1504/clip-retrieval', 0.5981614589691162, 'ml', 2), ('alibaba/easynlp', 0.5683876872062683, 'nlp', 2), ('google-research/electra', 0.5659348964691162, 'ml-dl', 1), ('microsoft/unilm', 0.5614645481109619, 'nlp', 0), ('salesforce/blip', 0.5517219305038452, 'diffusion', 0), ('yueyu1030/attrprompt', 0.5419546961784363, 'llm', 0), ('lucidrains/imagen-pytorch', 0.5373484492301941, 'ml-dl', 1), ('ofa-sys/ofa', 0.5293337106704712, 'llm', 0), ('saharmor/dalle-playground', 0.5254179239273071, 'diffusion', 1), ('compvis/stable-diffusion', 0.5251467227935791, 'diffusion', 0), ('openai/finetune-transformer-lm', 0.5225598812103271, 'llm', 0), ('lucidrains/deep-daze', 0.5211201906204224, 'ml', 1), ('nomic-ai/nomic', 0.5130395889282227, 'nlp', 0), ('nvlabs/prismer', 0.5122661590576172, 'diffusion', 0), ('jina-ai/finetuner', 0.505680501461029, 'ml', 0), ('extreme-bert/extreme-bert', 0.5033907890319824, 'llm', 2)] | 20 | 4 | null | 0.04 | 38 | 7 | 37 | 6 | 0 | 0 | 0 | 38 | 47 | 90 | 1.2 | 58 |
103 | ml-ops | https://github.com/spotify/luigi | [] | null | [] | [] | null | null | null | spotify/luigi | luigi | 17,022 | 2,388 | 477 | Python | null | Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in. | spotify | 2024-01-13 | 2012-09-20 | 592 | 28.718727 | https://avatars.githubusercontent.com/u/251374?v=4 | Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in. | ['hadoop', 'luigi', 'orchestration-framework', 'scheduling'] | ['hadoop', 'luigi', 'orchestration-framework', 'scheduling'] | 2024-01-08 | [('backtick-se/cowait', 0.5577235221862793, 'util', 0), ('dagster-io/dagster', 0.5423729419708252, 'ml-ops', 0), ('apache/spark', 0.537491500377655, 'data', 0), ('flyteorg/flyte', 0.5278602242469788, 'ml-ops', 0), ('ploomber/ploomber', 0.5267884135246277, 'ml-ops', 0), ('kestra-io/kestra', 0.5256256461143494, 'ml-ops', 0), ('fastai/fastcore', 0.5237264037132263, 'util', 0), ('dagworks-inc/hamilton', 0.5168716907501221, 'ml-ops', 0), ('prefecthq/prefect', 0.5162726640701294, 'ml-ops', 0), ('fugue-project/fugue', 0.5144204497337341, 'pandas', 0), ('malloydata/malloy-py', 0.5109559893608093, 'data', 0), ('orchest/orchest', 0.5029619336128235, 'ml-ops', 0)] | 613 | 4 | null | 0.44 | 22 | 16 | 138 | 0 | 4 | 6 | 4 | 22 | 19 | 90 | 0.9 | 58 |
668 | diffusion | https://github.com/borisdayma/dalle-mini | [] | null | [] | [] | null | null | null | borisdayma/dalle-mini | dalle-mini | 14,484 | 1,186 | 110 | Python | https://www.craiyon.com | DALL·E Mini - Generate images from a text prompt | borisdayma | 2024-01-13 | 2021-07-03 | 134 | 107.744952 | null | DALL·E Mini - Generate images from a text prompt | [] | [] | 2023-08-22 | [('saharmor/dalle-playground', 0.7689334750175476, 'diffusion', 0), ('lucidrains/deep-daze', 0.5611160397529602, 'ml', 0), ('laion-ai/dalle2-laion', 0.5235878229141235, 'diffusion', 0), ('1j01/textual-paint', 0.510983943939209, 'term', 0), ('thudm/cogvideo', 0.5106388926506042, 'ml', 0), ('openai/image-gpt', 0.5032017827033997, 'llm', 0)] | 28 | 7 | null | 0.27 | 3 | 0 | 31 | 5 | 0 | 2 | 2 | 3 | 3 | 90 | 1 | 58 |
1,473 | web | https://github.com/getpelican/pelican | [] | null | [] | [] | null | null | null | getpelican/pelican | pelican | 11,956 | 1,832 | 339 | Python | https://getpelican.com | Static site generator that supports Markdown and reST syntax. Powered by Python. | getpelican | 2024-01-13 | 2010-10-16 | 693 | 17.241862 | https://avatars.githubusercontent.com/u/2043492?v=4 | Static site generator that supports Markdown and reST syntax. Powered by Python. | ['pelican', 'static-site-generator'] | ['pelican', 'static-site-generator'] | 2024-01-12 | [('python-markdown/markdown', 0.6716626882553101, 'util', 0), ('mkdocs/mkdocs', 0.5778642296791077, 'util', 1), ('sphinx-doc/sphinx', 0.5320377349853516, 'util', 0), ('google/latexify_py', 0.5140236020088196, 'util', 0), ('instagram/monkeytype', 0.5085812211036682, 'typing', 0)] | 454 | 6 | null | 2.4 | 141 | 110 | 161 | 0 | 2 | 5 | 2 | 141 | 258 | 90 | 1.8 | 58 |
1,176 | llm | https://github.com/databrickslabs/dolly | [] | null | [] | [] | null | null | null | databrickslabs/dolly | dolly | 10,687 | 1,161 | 132 | Python | https://www.databricks.com/blog/2023/03/24/hello-dolly-democratizing-magic-chatgpt-open-models.html | Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform | databrickslabs | 2024-01-13 | 2023-03-24 | 44 | 239.772436 | https://avatars.githubusercontent.com/u/49501376?v=4 | Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform | ['chatbot', 'databricks', 'dolly', 'gpt'] | ['chatbot', 'databricks', 'dolly', 'gpt'] | 2023-06-30 | [('lm-sys/fastchat', 0.6816812753677368, 'llm', 1), ('rasahq/rasa', 0.6492189168930054, 'llm', 1), ('microsoft/autogen', 0.6176787614822388, 'llm', 2), ('deeppavlov/deeppavlov', 0.5981650352478027, 'nlp', 1), ('huggingface/text-generation-inference', 0.5939000248908997, 'llm', 1), ('infinitylogesh/mutate', 0.5938010811805725, 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0.5030844807624817, 'llm', 0), ('prefecthq/marvin', 0.5005607008934021, 'nlp', 1), ('iryna-kondr/scikit-llm', 0.5001913905143738, 'llm', 0), ('night-chen/toolqa', 0.5000602006912231, 'llm', 0)] | 14 | 3 | null | 1.31 | 3 | 1 | 10 | 7 | 0 | 0 | 0 | 3 | 2 | 90 | 0.7 | 58 |
1,798 | web | https://github.com/aws/chalice | [] | null | [] | [] | 1 | null | null | aws/chalice | chalice | 10,151 | 1,087 | 239 | Python | null | Python Serverless Microframework for AWS | aws | 2024-01-13 | 2016-05-27 | 400 | 25.341298 | https://avatars.githubusercontent.com/u/2232217?v=4 | Python Serverless Microframework for AWS | ['aws', 'aws-apigateway', 'aws-lambda', 'cloud', 'lambda', 'python27', 'serverless', 'serverless-framework'] | ['aws', 'aws-apigateway', 'aws-lambda', 'cloud', 'lambda', 'python27', 'serverless', 'serverless-framework'] | 2023-12-14 | [('nficano/python-lambda', 0.9045315980911255, 'util', 3), ('jordaneremieff/mangum', 0.677313506603241, 'web', 4), ('aws/aws-lambda-python-runtime-interface-client', 0.672527015209198, 'util', 0), ('boto/boto3', 0.66681307554245, 'util', 2), ('geeogi/async-python-lambda-template', 0.6311405301094055, 'template', 0), ('rpgreen/apilogs', 0.6253986954689026, 'util', 4), ('localstack/localstack', 0.5926650762557983, 'util', 2), ('pallets/quart', 0.5842033624649048, 'web', 0), ('falconry/falcon', 0.5833958387374878, 'web', 0), ('samuelcolvin/aioaws', 0.5785471200942993, 'data', 1), ('backtick-se/cowait', 0.5667223334312439, 'util', 0), ('pynamodb/pynamodb', 0.5429194569587708, 'data', 1), ('eventual-inc/daft', 0.5330685973167419, 'pandas', 0), ('awslabs/python-deequ', 0.5238412618637085, 'ml', 1), ('aws/serverless-application-model', 0.5237606167793274, 'util', 3), ('lithops-cloud/lithops', 0.5222293138504028, 'ml-ops', 1), ('aws/aws-sdk-pandas', 0.5215028524398804, 'pandas', 3), ('micropython/micropython', 0.5198830366134644, 'util', 0), ('pallets/flask', 0.5189753770828247, 'web', 0), ('neoteroi/blacksheep', 0.5133174657821655, 'web', 0), ('pyinfra-dev/pyinfra', 0.5128588080406189, 'util', 0), ('pylons/waitress', 0.5070593953132629, 'web', 0), ('developmentseed/geolambda', 0.5061563849449158, 'gis', 0), ('amzn/ion-python', 0.5045038461685181, 'data', 0), ('aws-samples/serverless-pdf-chat', 0.5006961226463318, 'llm', 1)] | 200 | 5 | null | 0.88 | 51 | 17 | 93 | 1 | 0 | 12 | 12 | 51 | 64 | 90 | 1.3 | 58 |
1,125 | util | https://github.com/secdev/scapy | [] | null | [] | [] | null | null | null | secdev/scapy | scapy | 9,682 | 2,001 | 228 | Python | https://scapy.net | Scapy: the Python-based interactive packet manipulation program & library. Supports Python 2 & Python 3. | secdev | 2024-01-13 | 2015-10-01 | 434 | 22.2721 | https://avatars.githubusercontent.com/u/14927208?v=4 | Scapy: the Python-based interactive packet manipulation program & library. Supports Python 2 & Python 3. | ['network', 'network-analysis', 'network-discovery', 'network-security', 'network-visualization', 'packet-analyser', 'packet-capture', 'packet-crafting', 'packet-sniffer', 'pcap', 'scapy', 'security', 'security-tools'] | ['network', 'network-analysis', 'network-discovery', 'network-security', 'network-visualization', 'packet-analyser', 'packet-capture', 'packet-crafting', 'packet-sniffer', 'pcap', 'scapy', 'security', 'security-tools'] | 2024-01-01 | [('hoffstadt/dearpygui', 0.5505430698394775, 'gui', 0), ('paramiko/paramiko', 0.5442431569099426, 'util', 0), ('pyca/pynacl', 0.5417189002037048, 'util', 0), ('alexmojaki/snoop', 0.5415452122688293, 'debug', 0), ('requests/toolbelt', 0.5415241122245789, 'util', 0), ('pyston/pyston', 0.5411231517791748, 'util', 0), ('pypy/pypy', 0.5363399982452393, 'util', 0), ('westhealth/pyvis', 0.5347074866294861, 'graph', 1), ('ethereum/web3.py', 0.5224668383598328, 'crypto', 0), ('py4j/py4j', 0.5051878690719604, 'util', 0), ('networkx/networkx', 0.5021397471427917, 'graph', 0)] | 446 | 4 | null | 3.81 | 267 | 229 | 101 | 1 | 0 | 64 | 64 | 267 | 140 | 90 | 0.5 | 58 |
285 | data | https://github.com/simonw/datasette | [] | null | [] | [] | 1 | null | null | simonw/datasette | datasette | 8,614 | 623 | 102 | Python | https://datasette.io | An open source multi-tool for exploring and publishing data | simonw | 2024-01-13 | 2017-10-23 | 327 | 26.331004 | null | An open source multi-tool for exploring and publishing data | ['asgi', 'automatic-api', 'csv', 'datasets', 'datasette', 'datasette-io', 'docker', 'json', 'sql', 'sqlite'] | ['asgi', 'automatic-api', 'csv', 'datasets', 'datasette', 'datasette-io', 'docker', 'json', 'sql', 'sqlite'] | 2024-01-12 | [('airbytehq/airbyte', 0.663290798664093, 'data', 0), ('meltano/meltano', 0.6087267398834229, 'ml-ops', 0), ('saulpw/visidata', 0.6051476001739502, 'term', 3), ('airbnb/omniduct', 0.6034160256385803, 'data', 0), ('zenodo/zenodo', 0.6021542549133301, 'util', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5789318084716797, 'template', 2), ('orchest/orchest', 0.5611031651496887, 'ml-ops', 1), ('unstructured-io/unstructured-api', 0.5543832778930664, 'data', 0), ('dagster-io/dagster', 0.5505277514457703, 'ml-ops', 0), ('tiangolo/sqlmodel', 0.5402882695198059, 'data', 2), ('ploomber/ploomber', 0.5322346091270447, 'ml-ops', 0), ('starlite-api/starlite', 0.526665985584259, 'web', 1), ('polyaxon/datatile', 0.525797963142395, 'pandas', 0), ('aws/aws-sdk-pandas', 0.525142252445221, 'pandas', 0), ('intake/intake', 0.5237489938735962, 'data', 0), ('falconry/falcon', 0.5216467380523682, 'web', 1), ('piccolo-orm/piccolo_admin', 0.5212988257408142, 'data', 2), ('streamlit/streamlit', 0.5206021666526794, 'viz', 0), ('plotly/dash', 0.5204837918281555, 'viz', 0), ('coleifer/peewee', 0.5180539488792419, 'data', 1), ('mattbierbaum/arxiv-public-datasets', 0.5164351463317871, 'data', 0), ('google/ml-metadata', 0.5161576271057129, 'ml-ops', 0), ('holoviz/panel', 0.5158277153968811, 'viz', 0), ('mage-ai/mage-ai', 0.5153981447219849, 'ml-ops', 1), ('airbnb/knowledge-repo', 0.5094085335731506, 'data', 0), ('darribas/gds_env', 0.5070315599441528, 'gis', 1), ('hyperqueryhq/whale', 0.5066918134689331, 'data', 0), ('mito-ds/monorepo', 0.5057903528213501, 'jupyter', 0), ('whylabs/whylogs', 0.5017004609107971, 'util', 0), ('python-odin/odin', 0.5009411573410034, 'util', 2)] | 75 | 4 | null | 2.62 | 67 | 20 | 76 | 0 | 10 | 23 | 10 | 67 | 95 | 90 | 1.4 | 58 |
1,308 | study | https://github.com/mooler0410/llmspracticalguide | ['awesome'] | null | [] | [] | null | null | null | mooler0410/llmspracticalguide | LLMsPracticalGuide | 7,737 | 583 | 168 | null | https://arxiv.org/abs/2304.13712v2 | A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers) | mooler0410 | 2024-01-14 | 2023-04-23 | 40 | 192.053191 | null | A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers) | ['large-language-models', 'natural-language-processing', 'nlp', 'survey'] | ['awesome', 'large-language-models', 'natural-language-processing', 'nlp', 'survey'] | 2023-08-06 | [('salesforce/xgen', 0.6607375741004944, 'llm', 2), ('eugeneyan/open-llms', 0.6558331847190857, 'study', 2), ('explosion/spacy-llm', 0.6550344228744507, 'llm', 3), ('dylanhogg/llmgraph', 0.6462394595146179, 'ml', 0), ('young-geng/easylm', 0.6447182893753052, 'llm', 2), ('argilla-io/argilla', 0.6409274935722351, 'nlp', 2), ('paddlepaddle/paddlenlp', 0.632652759552002, 'llm', 1), ('confident-ai/deepeval', 0.6305698156356812, 'testing', 0), ('hannibal046/awesome-llm', 0.6038196682929993, 'study', 1), ('llmware-ai/llmware', 0.6028851270675659, 'llm', 2), ('night-chen/toolqa', 0.6017274260520935, 'llm', 1), ('nomic-ai/gpt4all', 0.6006626486778259, 'llm', 0), ('ibm/dromedary', 0.5917999148368835, 'llm', 0), ('eleutherai/the-pile', 0.5788910984992981, 'data', 0), ('salesforce/codet5', 0.5782813429832458, 'nlp', 1), ('alpha-vllm/llama2-accessory', 0.5765708088874817, 'llm', 0), ('hiyouga/llama-efficient-tuning', 0.5758503079414368, 'llm', 1), ('hiyouga/llama-factory', 0.575850248336792, 'llm', 1), ('microsoft/torchscale', 0.5727461576461792, 'llm', 1), ('lianjiatech/belle', 0.5725797414779663, 'llm', 0), ('deepset-ai/haystack', 0.5716323256492615, 'llm', 2), ('hegelai/prompttools', 0.5667575001716614, 'llm', 1), ('tigerlab-ai/tiger', 0.5661339163780212, 'llm', 1), ('juncongmoo/pyllama', 0.5613843202590942, 'llm', 0), ('ray-project/ray-llm', 0.5559900999069214, 'llm', 1), ('agenta-ai/agenta', 0.5545148849487305, 'llm', 1), ('bobazooba/xllm', 0.5522361397743225, 'llm', 1), ('infinitylogesh/mutate', 0.5493302345275879, 'nlp', 0), ('nebuly-ai/nebullvm', 0.5461376905441284, 'perf', 1), ('microsoft/generative-ai-for-beginners', 0.5448139309883118, 'study', 0), ('tatsu-lab/stanford_alpaca', 0.5418017506599426, 'llm', 0), ('explosion/spacy-models', 0.5413009524345398, 'nlp', 2), ('cg123/mergekit', 0.5390522480010986, 'llm', 0), ('microsoft/jarvis', 0.5358785390853882, 'llm', 0), ('vllm-project/vllm', 0.5348982810974121, 'llm', 0), ('iryna-kondr/scikit-llm', 0.5321641564369202, 'llm', 0), ('jina-ai/thinkgpt', 0.5296755433082581, 'llm', 0), ('aiwaves-cn/agents', 0.5291845202445984, 'nlp', 0), ('epfllm/meditron', 0.5282127261161804, 'llm', 0), ('whitead/paper-qa', 0.5275523066520691, 'llm', 1), ('lexpredict/lexpredict-lexnlp', 0.525945782661438, 'nlp', 1), ('citadel-ai/langcheck', 0.5259177088737488, 'llm', 0), ('spcl/graph-of-thoughts', 0.5230525732040405, 'llm', 1), ('predibase/llm_distillation_playbook', 0.5229454040527344, 'llm', 0), ('nltk/nltk', 0.5214924812316895, 'nlp', 2), ('shishirpatil/gorilla', 0.5199465751647949, 'llm', 0), ('nat/openplayground', 0.5199169516563416, 'llm', 0), ('next-gpt/next-gpt', 0.5197857022285461, 'llm', 1), ('bentoml/openllm', 0.516433596611023, 'ml-ops', 0), ('bigscience-workshop/petals', 0.511151909828186, 'data', 2), ('microsoft/autogen', 0.5106921792030334, 'llm', 0), ('bigscience-workshop/biomedical', 0.5104791522026062, 'data', 0), ('graykode/nlp-tutorial', 0.510050356388092, 'study', 2), ('deep-diver/pingpong', 0.5093730688095093, 'llm', 0), ('artidoro/qlora', 0.5064951181411743, 'llm', 0), ('lm-sys/fastchat', 0.5060816407203674, 'llm', 0), ('neuml/txtai', 0.5057186484336853, 'nlp', 2), ('intel/intel-extension-for-transformers', 0.5048488974571228, 'perf', 0), ('allenai/allennlp', 0.5047245025634766, 'nlp', 2), ('zilliztech/gptcache', 0.5039639472961426, 'llm', 0), ('guidance-ai/guidance', 0.5038110613822937, 'llm', 0), ('hwchase17/langchain', 0.5019939541816711, 'llm', 0), ('freedomintelligence/llmzoo', 0.5019903182983398, 'llm', 0), ('microsoft/unilm', 0.5018056631088257, 'nlp', 1)] | 13 | 6 | null | 1.67 | 7 | 1 | 9 | 5 | 0 | 0 | 0 | 7 | 2 | 90 | 0.3 | 58 |
710 | util | https://github.com/jazzband/pip-tools | [] | null | [] | [] | null | null | null | jazzband/pip-tools | pip-tools | 7,269 | 607 | 104 | Python | https://pip-tools.rtfd.io | A set of tools to keep your pinned Python dependencies fresh. | jazzband | 2024-01-13 | 2012-09-10 | 594 | 12.234431 | https://avatars.githubusercontent.com/u/15129049?v=4 | A set of tools to keep your pinned Python dependencies fresh. | ['hashes', 'lockfile', 'packaging', 'pip', 'pip-compile', 'pip-tools', 'requirements', 'setuptools'] | ['hashes', 'lockfile', 'packaging', 'pip', 'pip-compile', 'pip-tools', 'requirements', 'setuptools'] | 2024-01-05 | [('pdm-project/pdm', 0.6316167116165161, 'util', 1), ('thoth-station/micropipenv', 0.6279821991920471, 'util', 2), ('python-poetry/poetry', 0.5958384871482849, 'util', 1), ('pypa/hatch', 0.5882735848426819, 'util', 1), ('indygreg/pyoxidizer', 0.5879077315330505, 'util', 1), ('pypi/warehouse', 0.5816731452941895, 'util', 0), ('pyupio/safety', 0.5792787671089172, 'security', 0), ('mitsuhiko/rye', 0.5770611763000488, 'util', 1), ('tezromach/python-package-template', 0.5716038346290588, 'template', 0), ('pypa/pipenv', 0.5539312958717346, 'util', 2), ('pomponchik/instld', 0.5494071245193481, 'util', 1), ('pypa/flit', 0.5470367670059204, 'util', 1), ('omry/omegaconf', 0.527951180934906, 'util', 0), ('mkdocstrings/griffe', 0.5269049406051636, 'util', 0), ('dosisod/refurb', 0.5137325525283813, 'util', 0), ('trailofbits/pip-audit', 0.5135653614997864, 'security', 1), ('ofek/pyapp', 0.5037299394607544, 'util', 1)] | 203 | 6 | null | 3.46 | 73 | 41 | 138 | 0 | 8 | 11 | 8 | 73 | 204 | 90 | 2.8 | 58 |
1,216 | util | https://github.com/googlecloudplatform/python-docs-samples | [] | null | [] | [] | null | null | null | googlecloudplatform/python-docs-samples | python-docs-samples | 6,777 | 6,352 | 388 | Jupyter Notebook | null | Code samples used on cloud.google.com | googlecloudplatform | 2024-01-13 | 2015-05-04 | 456 | 14.857188 | https://avatars.githubusercontent.com/u/2810941?v=4 | Code samples used on cloud.google.com | ['samples'] | ['samples'] | 2024-01-12 | [('googlecloudplatform/vertex-ai-samples', 0.5574522018432617, 'ml', 1)] | 591 | 4 | null | 32.98 | 467 | 365 | 106 | 0 | 0 | 0 | 0 | 466 | 602 | 90 | 1.3 | 58 |
1,345 | llm | https://github.com/bhaskatripathi/pdfgpt | [] | null | [] | [] | null | null | null | bhaskatripathi/pdfgpt | pdfGPT | 6,422 | 805 | 48 | Python | https://bhaskartripathi-pdfgpt-turbo.hf.space | PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot! | bhaskatripathi | 2024-01-13 | 2023-03-07 | 47 | 136.638298 | null | PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot! | ['chatpdf', 'chatwithpdf', 'pdfgpt'] | ['chatpdf', 'chatwithpdf', 'pdfgpt'] | 2023-09-04 | [('mayooear/gpt4-pdf-chatbot-langchain', 0.6926714777946472, 'llm', 0), ('h2oai/h2ogpt', 0.5438480377197266, 'llm', 0), ('minimaxir/simpleaichat', 0.5324260592460632, 'llm', 0), ('run-llama/rags', 0.5228466987609863, 'llm', 0), ('jorisschellekens/borb', 0.5003618597984314, 'util', 0)] | 11 | 4 | null | 2.06 | 11 | 6 | 10 | 4 | 0 | 0 | 0 | 11 | 14 | 90 | 1.3 | 58 |
545 | ml | https://github.com/open-mmlab/mmediting | [] | null | [] | [] | null | null | null | open-mmlab/mmediting | mmagic | 6,233 | 1,032 | 98 | Jupyter Notebook | https://mmagic.readthedocs.io/en/latest/ | OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc. | open-mmlab | 2024-01-14 | 2019-08-23 | 231 | 26.916101 | https://avatars.githubusercontent.com/u/10245193?v=4 | OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc. | ['aigc', 'computer-vision', 'deep-learning', 'diffusion', 'diffusion-models', 'generative-adversarial-network', 'generative-ai', 'image-editing', 'image-generation', 'image-processing', 'image-synthesis', 'inpainting', 'matting', 'pytorch', 'super-resolution', 'text2image', 'video-frame-interpolation', 'video-interpolation', 'video-super-resolution'] | ['aigc', 'computer-vision', 'deep-learning', 'diffusion', 'diffusion-models', 'generative-adversarial-network', 'generative-ai', 'image-editing', 'image-generation', 'image-processing', 'image-synthesis', 'inpainting', 'matting', 'pytorch', 'super-resolution', 'text2image', 'video-frame-interpolation', 'video-interpolation', 'video-super-resolution'] | 2024-01-10 | [('roboflow/supervision', 0.6228029727935791, 'ml', 4), ('albumentations-team/albumentations', 0.5985205769538879, 'ml-dl', 2), ('invoke-ai/invokeai', 0.5879208445549011, 'diffusion', 2), ('lucidrains/imagen-pytorch', 0.5784053206443787, 'ml-dl', 1), ('automatic1111/stable-diffusion-webui', 0.5722965002059937, 'diffusion', 5), ('sanster/lama-cleaner', 0.5644564032554626, 'ml-dl', 2), ('bentoml/bentoml', 0.5629596710205078, 'ml-ops', 2), ('huggingface/datasets', 0.5629530549049377, 'nlp', 3), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5617620944976807, 'web', 0), ('open-mmlab/mmsegmentation', 0.5589426755905151, 'ml', 1), ('rwightman/pytorch-image-models', 0.5570010542869568, 'ml-dl', 1), ('xpixelgroup/basicsr', 0.5552972555160522, 'ml-dl', 2), ('lucidrains/deep-daze', 0.5528916716575623, 'ml', 1), ('nvlabs/gcvit', 0.5518020987510681, 'diffusion', 1), ('saharmor/dalle-playground', 0.5508294105529785, 'diffusion', 0), ('lutzroeder/netron', 0.5503832101821899, 'ml', 2), ('aleju/imgaug', 0.5496745109558105, 'ml', 1), ('nateraw/stable-diffusion-videos', 0.5489683747291565, 'diffusion', 0), ('awslabs/autogluon', 0.5436397194862366, 'ml', 3), ('activeloopai/deeplake', 0.5429714918136597, 'ml-ops', 4), ('openai/image-gpt', 0.5370244383811951, 'llm', 0), ('luodian/otter', 0.53682941198349, 'llm', 1), ('davidadsp/generative_deep_learning_2nd_edition', 0.5358924269676208, 'study', 3), ('idea-research/grounded-segment-anything', 0.5329544544219971, 'llm', 1), ('microsoft/generative-ai-for-beginners', 0.532807469367981, 'study', 1), ('iperov/deepfacelab', 0.5308938026428223, 'ml-dl', 1), ('mosaicml/composer', 0.5261213183403015, 'ml-dl', 2), ('ddbourgin/numpy-ml', 0.5251216292381287, 'ml', 0), ('deci-ai/super-gradients', 0.5221906900405884, 'ml-dl', 3), ('fepegar/torchio', 0.5203762650489807, 'ml-dl', 2), ('carson-katri/dream-textures', 0.5198704600334167, 'diffusion', 1), ('thudm/cogvideo', 0.5184540748596191, 'ml', 0), ('roboflow/notebooks', 0.5162927508354187, 'study', 3), ('chenyangqiqi/fatezero', 0.5141303539276123, 'diffusion', 1), ('alibaba/easynlp', 0.5134133696556091, 'nlp', 2), ('tensorflow/tensorflow', 0.5129084587097168, 'ml-dl', 1), ('lucidrains/dalle2-pytorch', 0.5127325654029846, 'diffusion', 1), ('espnet/espnet', 0.5127143859863281, 'nlp', 2), ('blakeblackshear/frigate', 0.5040640234947205, 'util', 0), ('promptslab/awesome-prompt-engineering', 0.5029655694961548, 'study', 1), ('zulko/moviepy', 0.5014966726303101, 'util', 0), ('huggingface/autotrain-advanced', 0.5010733008384705, 'ml', 1)] | 126 | 4 | null | 5.38 | 71 | 44 | 54 | 0 | 8 | 6 | 8 | 71 | 57 | 90 | 0.8 | 58 |
1,295 | ml-ops | https://github.com/bentoml/bentoml | [] | null | [] | [] | null | null | null | bentoml/bentoml | BentoML | 6,093 | 692 | 72 | Python | https://bentoml.com | Build Production-Grade AI Applications | bentoml | 2024-01-13 | 2019-04-02 | 252 | 24.178571 | https://avatars.githubusercontent.com/u/49176046?v=4 | Build Production-Grade AI Applications | ['ai', 'ai-infra', 'bentoml', 'deep-learning', 'generative-ai', 'inference-api', 'kubernetes', 'llmops', 'lmops', 'machine-learning', 'microservices', 'ml-platform', 'mlops', 'model-deployment', 'model-inference', 'model-management', 'model-serving', 'multimodal-deep-learning'] | ['ai', 'ai-infra', 'bentoml', 'deep-learning', 'generative-ai', 'inference-api', 'kubernetes', 'llmops', 'lmops', 'machine-learning', 'microservices', 'ml-platform', 'mlops', 'model-deployment', 'model-inference', 'model-management', 'model-serving', 'multimodal-deep-learning'] | 2024-01-11 | [('hpcaitech/colossalai', 0.719754159450531, 'llm', 2), 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626 | util | https://github.com/pyca/cryptography | [] | null | [] | [] | null | null | null | pyca/cryptography | cryptography | 6,009 | 1,735 | 125 | Python | https://cryptography.io | cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. | pyca | 2024-01-14 | 2013-08-07 | 546 | 10.988245 | https://avatars.githubusercontent.com/u/5615737?v=4 | cryptography is a package designed to expose cryptographic primitives and recipes to Python developers. | ['cryptography'] | ['cryptography'] | 2024-01-14 | [('legrandin/pycryptodome', 0.8198734521865845, 'util', 1), ('pyca/pynacl', 0.659361720085144, 'util', 1), ('1200wd/bitcoinlib', 0.6551878452301025, 'crypto', 0), ('primal100/pybitcointools', 0.6024011373519897, 'crypto', 0), ('pypy/pypy', 0.5772532224655151, 'util', 0), ('man-c/pycoingecko', 0.5643881559371948, 'crypto', 0), ('pyupio/safety', 0.5316013097763062, 'security', 0), ('pyston/pyston', 0.5291821360588074, 'util', 0), ('pytoolz/toolz', 0.5245878100395203, 'util', 0), ('aswinnnn/pyscan', 0.5230307579040527, 'security', 0), ('sympy/sympy', 0.518089234828949, 'math', 0), ('paramiko/paramiko', 0.5152232646942139, 'util', 0), ('ta-lib/ta-lib-python', 0.5043237209320068, 'finance', 0), ('mkdocstrings/griffe', 0.5040481090545654, 'util', 0)] | 303 | 4 | null | 32.37 | 542 | 518 | 127 | 0 | 0 | 12 | 12 | 542 | 303 | 90 | 0.6 | 58 |
1,534 | ml-interpretability | https://github.com/interpretml/interpret | ['interpretability'] | null | [] | [] | null | null | null | interpretml/interpret | interpret | 5,868 | 704 | 141 | C++ | https://interpret.ml/docs | Fit interpretable models. Explain blackbox machine learning. | interpretml | 2024-01-13 | 2019-05-03 | 247 | 23.70225 | https://avatars.githubusercontent.com/u/27173223?v=4 | Fit interpretable models. Explain blackbox machine learning. | ['ai', 'artificial-intelligence', 'bias', 'blackbox', 'differential-privacy', 'explainability', 'explainable-ai', 'explainable-ml', 'gradient-boosting', 'iml', 'interpretability', 'interpretable-ai', 'interpretable-machine-learning', 'interpretable-ml', 'interpretml', 'machine-learning', 'scikit-learn', 'transparency', 'xai'] | ['ai', 'artificial-intelligence', 'bias', 'blackbox', 'differential-privacy', 'explainability', 'explainable-ai', 'explainable-ml', 'gradient-boosting', 'iml', 'interpretability', 'interpretable-ai', 'interpretable-machine-learning', 'interpretable-ml', 'interpretml', 'machine-learning', 'scikit-learn', 'transparency', 'xai'] | 2024-01-14 | [('csinva/imodels', 0.7508851289749146, 'ml', 7), ('oegedijk/explainerdashboard', 0.6743864417076111, 'ml-interpretability', 1), ('xplainable/xplainable', 0.6733729839324951, 'ml-interpretability', 4), ('seldonio/alibi', 0.6674531102180481, 'ml-interpretability', 3), ('maif/shapash', 0.6510236859321594, 'ml', 5), ('marcotcr/lime', 0.634106457233429, 'ml-interpretability', 1), ('tensorflow/lucid', 0.626980721950531, 'ml-interpretability', 2), ('pair-code/lit', 0.6197747588157654, 'ml-interpretability', 1), ('pytorch/captum', 0.6127338409423828, 'ml-interpretability', 3), ('cdpierse/transformers-interpret', 0.6050029993057251, 'ml-interpretability', 3), ('slundberg/shap', 0.5977214574813843, 'ml-interpretability', 4), ('mosaicml/composer', 0.5779016613960266, 'ml-dl', 1), ('rafiqhasan/auto-tensorflow', 0.5614568591117859, 'ml-dl', 1), ('teamhg-memex/eli5', 0.5581210851669312, 'ml', 2), ('eleutherai/pythia', 0.5574303269386292, 'ml-interpretability', 2), ('giskard-ai/giskard', 0.5559372305870056, 'data', 3), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.542955756187439, 'study', 3), ('explosion/thinc', 0.5354365706443787, 'ml-dl', 3), ('linkedin/fasttreeshap', 0.5312417149543762, 'ml', 3), ('hpcaitech/colossalai', 0.5297350883483887, 'llm', 1), ('arize-ai/phoenix', 0.5245933532714844, 'ml-interpretability', 0), ('selfexplainml/piml-toolbox', 0.5234452486038208, 'ml-interpretability', 1), ('polyaxon/datatile', 0.5212517976760864, 'pandas', 1), ('ddbourgin/numpy-ml', 0.5201536417007446, 'ml', 2), ('bentoml/bentoml', 0.5196956992149353, 'ml-ops', 2), ('onnx/onnx', 0.5163048505783081, 'ml', 2), ('tensorflow/tensorflow', 0.5142463445663452, 'ml-dl', 1), ('nccr-itmo/fedot', 0.5118159651756287, 'ml-ops', 1), ('makcedward/nlpaug', 0.5114248394966125, 'nlp', 3), ('alirezadir/machine-learning-interview-enlightener', 0.5096079707145691, 'study', 2), ('carla-recourse/carla', 0.5091050863265991, 'ml', 5), ('lutzroeder/netron', 0.5063915848731995, 'ml', 2), ('whylabs/whylogs', 0.5045889019966125, 'util', 1), ('tensorflow/tensor2tensor', 0.5023159980773926, 'ml', 1), ('huggingface/datasets', 0.5013808608055115, 'nlp', 1), ('huggingface/autotrain-advanced', 0.500921368598938, 'ml', 1)] | 40 | 3 | null | 14.46 | 30 | 11 | 57 | 0 | 8 | 9 | 8 | 30 | 67 | 90 | 2.2 | 58 |
403 | perf | https://github.com/python-trio/trio | [] | null | [] | [] | null | null | null | python-trio/trio | trio | 5,713 | 316 | 85 | Python | https://trio.readthedocs.io | Trio – a friendly Python library for async concurrency and I/O | python-trio | 2024-01-13 | 2017-01-16 | 367 | 15.5607 | https://avatars.githubusercontent.com/u/26335827?v=4 | Trio – a friendly Python library for async concurrency and I/O | ['async', 'async-await', 'io', 'networking', 'structured-concurrency', 'trio'] | ['async', 'async-await', 'io', 'networking', 'structured-concurrency', 'trio'] | 2024-01-10 | [('agronholm/anyio', 0.8090512156486511, 'perf', 2), ('magicstack/uvloop', 0.6619237065315247, 'util', 3), ('alirn76/panther', 0.6534282565116882, 'web', 0), ('samuelcolvin/arq', 0.6487094759941101, 'data', 1), ('pallets/quart', 0.6473005414009094, 'web', 0), ('eventlet/eventlet', 0.6357116103172302, 'perf', 0), ('aio-libs/aiohttp', 0.6344983577728271, 'web', 1), ('sumerc/yappi', 0.6272547245025635, 'profiling', 0), ('tiangolo/asyncer', 0.6240719556808472, 'perf', 2), ('airtai/faststream', 0.6224059462547302, 'perf', 0), ('encode/httpx', 0.5947321057319641, 'web', 1), ('noxdafox/pebble', 0.5942329168319702, 'perf', 0), ('collerek/ormar', 0.5920240879058838, 'data', 0), ('python-greenlet/greenlet', 0.5789716839790344, 'perf', 0), ('joblib/joblib', 0.5737351179122925, 'util', 0), ('tox-dev/py-filelock', 0.5723570585250854, 'util', 0), ('tornadoweb/tornado', 0.5695123076438904, 'web', 0), ('geeogi/async-python-lambda-template', 0.5684411525726318, 'template', 0), ('timofurrer/awesome-asyncio', 0.5602687001228333, 'study', 0), ('miguelgrinberg/python-socketio', 0.5562794208526611, 'util', 0), ('klen/muffin', 0.5527318716049194, 'web', 1), ('neoteroi/blacksheep', 0.5497913956642151, 'web', 0), ('ipython/ipyparallel', 0.549788773059845, 'perf', 0), ('pytoolz/toolz', 0.5491801500320435, 'util', 0), ('fastai/fastcore', 0.5491400361061096, 'util', 0), ('pyston/pyston', 0.5414426922798157, 'util', 0), ('pypy/pypy', 0.5405836701393127, 'util', 0), ('fluentpython/example-code-2e', 0.5376577377319336, 'study', 0), ('encode/uvicorn', 0.5339199304580688, 'web', 0), ('bogdanp/dramatiq', 0.5322513580322266, 'util', 0), ('python-cachier/cachier', 0.528437077999115, 'perf', 0), ('joblib/loky', 0.5253786444664001, 'perf', 0), ('klen/py-frameworks-bench', 0.5250015258789062, 'perf', 0), ('micropython/micropython', 0.5247344970703125, 'util', 0), ('encode/starlette', 0.5227438807487488, 'web', 1), ('dgilland/cacheout', 0.5188122987747192, 'perf', 0), ('agronholm/apscheduler', 0.5111809968948364, 'util', 0), ('hyperopt/hyperopt', 0.510098934173584, 'ml', 0), ('dask/dask', 0.5067204236984253, 'perf', 0), ('samuelcolvin/watchfiles', 0.5042653679847717, 'util', 0), ('backtick-se/cowait', 0.5035473704338074, 'util', 0), ('samuelcolvin/aioaws', 0.5013687610626221, 'data', 0)] | 154 | 3 | null | 7.71 | 153 | 107 | 85 | 0 | 5 | 4 | 5 | 153 | 482 | 90 | 3.2 | 58 |
944 | security | https://github.com/stamparm/maltrail | [] | null | [] | [] | null | null | null | stamparm/maltrail | maltrail | 5,548 | 1,017 | 229 | Python | null | Malicious traffic detection system | stamparm | 2024-01-14 | 2014-12-04 | 477 | 11.613636 | null | Malicious traffic detection system | ['attack-detection', 'intrusion-detection', 'malware', 'network-monitoring', 'security', 'sensor'] | ['attack-detection', 'intrusion-detection', 'malware', 'network-monitoring', 'security', 'sensor'] | 2024-01-13 | [] | 47 | 4 | null | 305.44 | 35 | 30 | 111 | 0 | 12 | 6 | 12 | 35 | 48 | 90 | 1.4 | 58 |
547 | ml | https://github.com/open-mmlab/mmcv | ['computer-vision'] | null | [] | [] | null | null | null | open-mmlab/mmcv | mmcv | 5,409 | 1,575 | 86 | Python | https://mmcv.readthedocs.io/en/latest/ | OpenMMLab Computer Vision Foundation | open-mmlab | 2024-01-14 | 2018-08-22 | 283 | 19.05536 | https://avatars.githubusercontent.com/u/10245193?v=4 | OpenMMLab Computer Vision Foundation | [] | ['computer-vision'] | 2024-01-07 | [('open-mmlab/mmdetection', 0.6718772649765015, 'ml', 0), ('open-mmlab/mmsegmentation', 0.6504673361778259, 'ml', 0), ('deci-ai/super-gradients', 0.5693687796592712, 'ml-dl', 1), ('luispedro/mahotas', 0.5330637693405151, 'viz', 1), ('roboflow/supervision', 0.524324893951416, 'ml', 1)] | 260 | 7 | null | 1.87 | 91 | 52 | 66 | 0 | 5 | 20 | 5 | 91 | 146 | 90 | 1.6 | 58 |
1,666 | ml-ops | https://github.com/kestra-io/kestra | [] | null | [] | [] | 1 | null | null | kestra-io/kestra | kestra | 5,200 | 285 | 54 | Java | https://kestra.io | Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code. | kestra-io | 2024-01-14 | 2019-08-24 | 231 | 22.469136 | https://avatars.githubusercontent.com/u/59033362?v=4 | Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code. | ['data', 'data-engineering', 'data-integration', 'data-orchestration', 'data-orchestrator', 'data-pipeline', 'data-quality', 'elt', 'etl', 'low-code', 'orchestration', 'pipeline', 'reverse-etl', 'scheduler', 'workflow', 'workflow-engine'] | ['data', 'data-engineering', 'data-integration', 'data-orchestration', 'data-orchestrator', 'data-pipeline', 'data-quality', 'elt', 'etl', 'low-code', 'orchestration', 'pipeline', 'reverse-etl', 'scheduler', 'workflow', 'workflow-engine'] | 2024-01-12 | [('flyteorg/flyte', 0.7973306775093079, 'ml-ops', 2), ('dagster-io/dagster', 0.7322535514831543, 'ml-ops', 7), ('mage-ai/mage-ai', 0.6831650137901306, 'ml-ops', 8), ('prefecthq/server', 0.6529881954193115, 'util', 3), ('apache/airflow', 0.6468701362609863, 'ml-ops', 9), ('prefecthq/prefect', 0.6422749757766724, 'ml-ops', 6), ('airbytehq/airbyte', 0.6355409622192383, 'data', 7), ('orchest/orchest', 0.6342953443527222, 'ml-ops', 1), ('ploomber/ploomber', 0.6272913217544556, 'ml-ops', 2), ('astronomer/astro-sdk', 0.6130484342575073, 'ml-ops', 2), ('avaiga/taipy', 0.6105530858039856, 'data', 4), ('backtick-se/cowait', 0.5885079503059387, 'util', 2), ('meltano/meltano', 0.5790954232215881, 'ml-ops', 3), ('dagworks-inc/hamilton', 0.5751848816871643, 'ml-ops', 3), ('polyaxon/polyaxon', 0.561455249786377, 'ml-ops', 1), ('fugue-project/fugue', 0.5582082271575928, 'pandas', 0), ('zenml-io/zenml', 0.5403246879577637, 'ml-ops', 1), ('allegroai/clearml', 0.5374925136566162, 'ml-ops', 0), ('bodywork-ml/bodywork-core', 0.5349816083908081, 'ml-ops', 2), ('apache/spark', 0.5336428284645081, 'data', 0), ('getindata/kedro-kubeflow', 0.5321413278579712, 'ml-ops', 0), ('modin-project/modin', 0.5311633348464966, 'perf', 0), ('merantix-momentum/squirrel-core', 0.5266260504722595, 'ml', 0), ('spotify/luigi', 0.5256256461143494, 'ml-ops', 0), ('netflix/metaflow', 0.5250420570373535, 'ml-ops', 0), ('pathwaycom/pathway', 0.5241698026657104, 'data', 0), ('fastai/fastcore', 0.5094014406204224, 'util', 0), ('pytables/pytables', 0.5085448026657104, 'data', 0), ('linealabs/lineapy', 0.5073179602622986, 'jupyter', 0), ('pydoit/doit', 0.5050574541091919, 'util', 2), ('tiangolo/full-stack-fastapi-postgresql', 0.501535952091217, 'template', 0)] | 41 | 2 | null | 20.23 | 915 | 469 | 53 | 0 | 37 | 23 | 37 | 915 | 611 | 90 | 0.7 | 58 |
67 | util | https://github.com/pycqa/pylint | ['code-quality'] | null | [] | ['pylint'] | null | null | null | pycqa/pylint | pylint | 4,989 | 1,067 | 77 | Python | https://pylint.readthedocs.io/en/latest/ | It's not just a linter that annoys you! | pycqa | 2024-01-13 | 2015-12-09 | 424 | 11.742771 | https://avatars.githubusercontent.com/u/121692054?v=4 | It's not just a linter that annoys you! | ['code-quality', 'linter', 'pep8', 'static-analysis', 'static-code-analysis'] | ['code-quality', 'linter', 'pep8', 'static-analysis', 'static-code-analysis'] | 2024-01-10 | [('astral-sh/ruff', 0.569158136844635, 'util', 5), ('google/pytype', 0.5689358115196228, 'typing', 4), ('klen/pylama', 0.5042141675949097, 'util', 1), ('python/mypy', 0.5039985179901123, 'typing', 2)] | 553 | 3 | null | 15.12 | 288 | 145 | 99 | 0 | 21 | 23 | 21 | 288 | 524 | 90 | 1.8 | 58 |
815 | ml | https://github.com/project-monai/monai | [] | null | [] | [] | null | null | null | project-monai/monai | MONAI | 4,983 | 920 | 93 | Python | https://monai.io/ | AI Toolkit for Healthcare Imaging | project-monai | 2024-01-14 | 2019-10-11 | 224 | 22.188931 | https://avatars.githubusercontent.com/u/56449156?v=4 | AI Toolkit for Healthcare Imaging | ['deep-learning', 'healthcare-imaging', 'medical-image-computing', 'medical-image-processing', 'monai', 'pytorch'] | ['deep-learning', 'healthcare-imaging', 'medical-image-computing', 'medical-image-processing', 'monai', 'pytorch'] | 2024-01-12 | [('fepegar/torchio', 0.8480987548828125, 'ml-dl', 4), ('albumentations-team/albumentations', 0.5541568994522095, 'ml-dl', 1), ('tensorflow/tensorflow', 0.539412260055542, 'ml-dl', 1), ('microsoft/onnxruntime', 0.5315036773681641, 'ml', 2), ('lucidrains/medical-chatgpt', 0.5313103795051575, 'llm', 1), ('keras-team/keras', 0.5263016819953918, 'ml-dl', 2), ('oneil512/insight', 0.5232803225517273, 'ml', 0), ('open-mmlab/mmsegmentation', 0.5131828188896179, 'ml', 1), ('nvidia/deeplearningexamples', 0.5109444260597229, 'ml-dl', 2), ('huggingface/datasets', 0.5077080130577087, 'nlp', 2), ('tensorflow/tensor2tensor', 0.5071702599525452, 'ml', 1)] | 176 | 3 | null | 8.88 | 358 | 233 | 52 | 0 | 2 | 20 | 2 | 358 | 519 | 90 | 1.4 | 58 |
750 | util | https://github.com/pypa/hatch | ['package-manager', 'packaging'] | null | [] | [] | null | null | null | pypa/hatch | hatch | 4,939 | 281 | 49 | Python | https://hatch.pypa.io/latest/ | Modern, extensible Python project management | pypa | 2024-01-14 | 2017-05-31 | 347 | 14.198357 | https://avatars.githubusercontent.com/u/647025?v=4 | Modern, extensible Python project management | ['build', 'cli', 'packaging', 'plugin', 'versioning', 'virtualenv'] | ['build', 'cli', 'package-manager', 'packaging', 'plugin', 'versioning', 'virtualenv'] | 2024-01-13 | [('python-poetry/poetry', 0.7199224233627319, 'util', 2), ('pypa/pipenv', 0.7155768275260925, 'util', 2), ('mitsuhiko/rye', 0.7138620615005493, 'util', 2), ('indygreg/pyoxidizer', 0.7048346400260925, 'util', 2), ('pomponchik/instld', 0.6995571255683899, 'util', 1), ('pdm-project/pdm', 0.6953819394111633, 'util', 2), ('dosisod/refurb', 0.6656979322433472, 'util', 1), ('pypa/flit', 0.6373385787010193, 'util', 2), ('pypa/virtualenv', 0.6300379633903503, 'util', 1), ('pyenv/pyenv', 0.6283936500549316, 'util', 0), ('ofek/pyapp', 0.6210417747497559, 'util', 3), ('tezromach/python-package-template', 0.6175110936164856, 'template', 0), ('pypi/warehouse', 0.6159988641738892, 'util', 0), ('eugeneyan/python-collab-template', 0.613045871257782, 'template', 0), ('beeware/briefcase', 0.6087289452552795, 'util', 0), ('conda/conda-build', 0.5962553024291992, 'util', 0), ('pypa/build', 0.5941884517669678, 'util', 1), ('pyodide/micropip', 0.5937002897262573, 'util', 0), ('omry/omegaconf', 0.5926797986030579, 'util', 0), ('spack/spack', 0.592124879360199, 'util', 1), ('jazzband/pip-tools', 0.5882735848426819, 'util', 1), ('martinheinz/python-project-blueprint', 0.5873016119003296, 'template', 0), ('willmcgugan/textual', 0.5866153836250305, 'term', 1), ('tedivm/robs_awesome_python_template', 0.582638144493103, 'template', 0), ('eleutherai/pyfra', 0.5818159580230713, 'ml', 0), ('thoth-station/micropipenv', 0.5751578211784363, 'util', 0), ('pyscaffold/pyscaffold', 0.5699118971824646, 'template', 0), ('amaargiru/pyroad', 0.5697453618049622, 'study', 0), ('pypy/pypy', 0.5679408311843872, 'util', 0), ('regebro/pyroma', 0.5634012818336487, 'util', 1), ('mtkennerly/dunamai', 0.56247878074646, 'util', 2), ('pytables/pytables', 0.5594925880432129, 'data', 0), ('mamba-org/mamba', 0.5550651550292969, 'util', 2), ('hoffstadt/dearpygui', 0.5478973388671875, 'gui', 0), ('malloydata/malloy-py', 0.547518789768219, 'data', 0), ('conda/conda', 0.5469714999198914, 'util', 2), ('pyinfra-dev/pyinfra', 0.5454100966453552, 'util', 0), ('urwid/urwid', 0.5425727963447571, 'term', 0), ('pallets/flask', 0.5425235033035278, 'web', 0), ('python/cpython', 0.5416925549507141, 'util', 0), ('cython/cython', 0.5406709313392639, 'util', 0), ('pympler/pympler', 0.5399362444877625, 'perf', 0), ('samuelcolvin/python-devtools', 0.5391005277633667, 'debug', 0), ('mamba-org/gator', 0.5378934741020203, 'jupyter', 0), ('backtick-se/cowait', 0.5353484153747559, 'util', 0), ('landscapeio/prospector', 0.5343112945556641, 'util', 0), ('exaloop/codon', 0.5342748761177063, 'perf', 0), ('rubik/radon', 0.5330091714859009, 'util', 1), ('pypa/gh-action-pypi-publish', 0.5319401025772095, 'util', 0), ('libtcod/python-tcod', 0.5316311120986938, 'gamedev', 0), ('google/gin-config', 0.5304906368255615, 'util', 0), ('erotemic/ubelt', 0.5291941165924072, 'util', 0), ('pytoolz/toolz', 0.5271018743515015, 'util', 0), ('pyo3/maturin', 0.5255593061447144, 'util', 1), ('mkdocstrings/griffe', 0.5250239968299866, 'util', 0), ('bottlepy/bottle', 0.5236046314239502, 'web', 0), ('kubeflow/fairing', 0.5211179256439209, 'ml-ops', 0), ('pypa/setuptools_scm', 0.5210332274436951, 'util', 2), ('mitmproxy/pdoc', 0.520322322845459, 'util', 0), ('citadel-ai/langcheck', 0.5197140574455261, 'llm', 0), ('google/python-fire', 0.5173959732055664, 'term', 1), ('trailofbits/pip-audit', 0.5167754292488098, 'security', 0), ('tox-dev/pipdeptree', 0.5165544152259827, 'util', 1), ('fastai/fastcore', 0.5164702534675598, 'util', 0), ('tiangolo/poetry-version-plugin', 0.5143115520477295, 'util', 1), ('orchest/orchest', 0.510188639163971, 'ml-ops', 0), ('psf/black', 0.5100483894348145, 'util', 0), ('scikit-build/scikit-build', 0.509085476398468, 'ml', 1), ('pypa/pipx', 0.5080375671386719, 'util', 1), ('prompt-toolkit/ptpython', 0.5076357126235962, 'util', 1), ('cookiecutter/cookiecutter', 0.5061737895011902, 'template', 0), ('grahamdumpleton/wrapt', 0.5048109292984009, 'util', 0), ('sqlalchemy/mako', 0.5044662356376648, 'template', 0), ('pyston/pyston', 0.5036124587059021, 'util', 0), ('ethereum/py-evm', 0.5026881694793701, 'crypto', 0), ('sourcery-ai/sourcery', 0.5025754570960999, 'util', 0), ('python-cachier/cachier', 0.502075731754303, 'perf', 0), ('jquast/blessed', 0.5016807913780212, 'term', 1)] | 54 | 6 | null | 3.71 | 238 | 173 | 81 | 0 | 18 | 16 | 18 | 238 | 511 | 90 | 2.1 | 58 |