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Update libs links (huggingface#1201)
* Update models-libraries.md links To improve UX we changed the links of the library to the Hub Docs ones * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Julien Chaumond <julien@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/hub/models-libraries.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> --------- Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: Julien Chaumond <julien@huggingface.co>
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‎docs/hub/models-libraries.md

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@@ -6,40 +6,40 @@ The table below summarizes the supported libraries and their level of integratio
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| Library | Description | Inference API | Widgets | Download from Hub | Push to Hub |
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|-----------------------------------------------------------------------------|--------------------------------------------------------------------------------------|---|---:|---|---|
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| [Adapter Transformers](https://github.com/Adapter-Hub/adapter-transformers) | Extends 🤗Transformers with Adapters. | ❌ | ❌ | ✅ | ✅ |
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| [AllenNLP](https://github.com/allenai/allennlp) | An open-source NLP research library, built on PyTorch. | ✅ | ✅ | ✅ | ❌ |
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| [Asteroid](https://github.com/asteroid-team/asteroid) | Pytorch-based audio source separation toolkit | ✅ | ✅ | ✅ | ❌ |
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| [BERTopic](https://github.com/MaartenGr/BERTopic) | BERTopic is a topic modeling library for text and images | ✅ | ✅ | ✅ | ✅ |
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| [Diffusers](https://github.com/huggingface/diffusers) | A modular toolbox for inference and training of diffusion models | ✅ | ✅ | ✅ | ✅ |
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| [Adapter Transformers](./adapter-transformers) | Extends 🤗Transformers with Adapters. | ❌ | ❌ | ✅ | ✅ |
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| [AllenNLP](./allennlp) | An open-source NLP research library, built on PyTorch. | ✅ | ✅ | ✅ | ❌ |
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| [Asteroid](./asteroid) | PyTorch-based audio source separation toolkit | ✅ | ✅ | ✅ | ❌ |
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| [BERTopic](./bertopic) | BERTopic is a topic modeling library for text and images | ✅ | ✅ | ✅ | ✅ |
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| [Diffusers](./diffusers) | A modular toolbox for inference and training of diffusion models | ✅ | ✅ | ✅ | ✅ |
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| [docTR](https://github.com/mindee/doctr) | Models and datasets for OCR-related tasks in PyTorch & TensorFlow | ✅ | ✅ | ✅ | ❌ |
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| [ESPnet](https://github.com/espnet/espnet) | End-to-end speech processing toolkit (e.g. TTS) | ✅ | ✅ | ✅ | ❌ |
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| [fastai](https://github.com/fastai/fastai) | Library to train fast and accurate models with state-of-the-art outputs. | ✅ | ✅ | ✅ | ✅ |
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| [ESPnet](./espnet) | End-to-end speech processing toolkit (e.g. TTS) | ✅ | ✅ | ✅ | ❌ |
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| [fastai](./fastai) | Library to train fast and accurate models with state-of-the-art outputs. | ✅ | ✅ | ✅ | ✅ |
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| [Keras](https://huggingface.co/docs/hub/keras) | Library that uses a consistent and simple API to build models leveraging TensorFlow and its ecosystem. | ❌ | ❌ | ✅ | ✅ |
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| [Flair](https://github.com/flairNLP/flair) | Very simple framework for state-of-the-art NLP. | ✅ | ✅ | ✅ | ✅ |
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| [Flair](./flair) | Very simple framework for state-of-the-art NLP. | ✅ | ✅ | ✅ | ✅ |
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| [MBRL-Lib](https://github.com/facebookresearch/mbrl-lib) | PyTorch implementations of MBRL Algorithms. | ❌ | ❌ | ✅ | ✅ |
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| [MidiTok](https://github.com/Natooz/MidiTok) | Tokenizers for symbolic music / MIDI files. | ❌ | ❌ | ✅ | ✅ |
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| [ML-Agents](https://github.com/huggingface/ml-agents) | Enables games and simulations made with Unity to serve as environments for training intelligent agents. | ❌ | ❌ | ✅ | ✅ |
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| [ML-Agents](./ml-agents) | Enables games and simulations made with Unity to serve as environments for training intelligent agents. | ❌ | ❌ | ✅ | ✅ |
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| [NeMo](https://github.com/NVIDIA/NeMo) | Conversational AI toolkit built for researchers | ✅ | ✅ | ✅ | ❌ |
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| [OpenCLIP](https://github.com/mlfoundations/open_clip) | Library for open-source implementation of OpenAI's CLIP | ❌ | ❌ | ✅ | ✅ |
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| [PaddleNLP](https://github.com/PaddlePaddle/PaddleNLP) | Easy-to-use and powerful NLP library built on PaddlePaddle | ✅ | ✅ | ✅ | ✅ |
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| [PEFT](https://github.com/huggingface/peft) | Cutting-edge Parameter Efficient Fine-tuning Library | ✅ | ✅ | ✅ | ✅ |
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| [OpenCLIP](./open_clip) | Library for open-source implementation of OpenAI's CLIP | ❌ | ❌ | ✅ | ✅ |
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| [PaddleNLP](./paddlenlp) | Easy-to-use and powerful NLP library built on PaddlePaddle | ✅ | ✅ | ✅ | ✅ |
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| [PEFT](./peft) | Cutting-edge Parameter Efficient Fine-tuning Library | ✅ | ✅ | ✅ | ✅ |
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| [Pyannote](https://github.com/pyannote/pyannote-audio) | Neural building blocks for speaker diarization. | ❌ | ❌ | ✅ | ❌ |
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| [PyCTCDecode](https://github.com/kensho-technologies/pyctcdecode) | Language model supported CTC decoding for speech recognition | ❌ | ❌ | ✅ | ❌ |
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| [Pythae](https://github.com/clementchadebec/benchmark_VAE) | Unified framework for Generative Autoencoders in Python | ❌ | ❌ | ✅ | ✅ |
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| [RL-Baselines3-Zoo](https://github.com/DLR-RM/rl-baselines3-zoo) | Training framework for Reinforcement Learning, using [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3).| ❌ | ✅ | ✅ | ✅ |
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| [Sample Factory](https://github.com/alex-petrenko/sample-factory) | Codebase for high throughput asynchronous reinforcement learning. | ❌ | ✅ | ✅ | ✅ |
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| [Sentence Transformers](https://github.com/UKPLab/sentence-transformers) | Compute dense vector representations for sentences, paragraphs, and images. | ✅ | ✅ | ✅ | ✅ |
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| [SetFit](https://github.com/huggingface/setfit) | Efficient few-shot text classification with Sentence Transformers | ✅ | ✅ | ✅ | ✅ |
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| [spaCy](https://github.com/explosion/spaCy) | Advanced Natural Language Processing in Python and Cython. | ✅ | ✅ | ✅ | ✅ |
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| [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) | Familiar, simple and state-of-the-art Named Entity Recognition. | ✅ | ✅ | ✅ | ✅ |
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| [RL-Baselines3-Zoo](./rl-baselines3-zoo) | Training framework for Reinforcement Learning, using [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3).| ❌ | ✅ | ✅ | ✅ |
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| [Sample Factory](./sample-factory) | Codebase for high throughput asynchronous reinforcement learning. | ❌ | ✅ | ✅ | ✅ |
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| [Sentence Transformers](./sentence-transformers) | Compute dense vector representations for sentences, paragraphs, and images. | ✅ | ✅ | ✅ | ✅ |
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| [SetFit](./setfit) | Efficient few-shot text classification with Sentence Transformers | ✅ | ✅ | ✅ | ✅ |
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| [spaCy](./spacy) | Advanced Natural Language Processing in Python and Cython. | ✅ | ✅ | ✅ | ✅ |
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| [SpanMarker](./span_marker) | Familiar, simple and state-of-the-art Named Entity Recognition. | ✅ | ✅ | ✅ | ✅ |
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| [Scikit Learn (using skops)](https://skops.readthedocs.io/en/stable/) | Machine Learning in Python. | ✅ | ✅ | ✅ | ✅ |
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| [Speechbrain](https://speechbrain.github.io/) | A PyTorch Powered Speech Toolkit. | ✅ | ✅ | ✅ | ❌ |
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| [Stable-Baselines3](https://github.com/DLR-RM/stable-baselines3) | Set of reliable implementations of deep reinforcement learning algorithms in PyTorch | ❌ | ✅ | ✅ | ✅ |
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| [Speechbrain](./speechbrain) | A PyTorch Powered Speech Toolkit. | ✅ | ✅ | ✅ | ❌ |
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| [Stable-Baselines3](./stable-baselines3) | Set of reliable implementations of deep reinforcement learning algorithms in PyTorch | ❌ | ✅ | ✅ | ✅ |
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| [TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS) | Real-time state-of-the-art speech synthesis architectures. | ❌ | ❌ | ✅ | ❌ |
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| [Timm](https://github.com/rwightman/pytorch-image-models) | Collection of image models, scripts, pretrained weights, etc. | ✅ | ✅ | ✅ | ✅ |
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| [Transformers](https://github.com/huggingface/transformers) | State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX | ✅ | ✅ | ✅ | ✅ |
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| [Transformers.js](https://github.com/xenova/transformers.js) | State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server! | ❌ | ❌ | ✅ | ❌ |
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| [Unity Sentis](https://unity.com/products/sentis) | Inference engine for the Unity 3D game engine | ❌ | ❌ | ❌ | ❌ |
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| [Timm](./timm) | Collection of image models, scripts, pretrained weights, etc. | ✅ | ✅ | ✅ | ✅ |
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| [Transformers](./transformers) | State-of-the-art Natural Language Processing for PyTorch, TensorFlow, and JAX | ✅ | ✅ | ✅ | ✅ |
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| [Transformers.js](./transformers-js) | State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server! | ❌ | ❌ | ✅ | ❌ |
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| [Unity Sentis](./unity-sentis) | Inference engine for the Unity 3D game engine | ❌ | ❌ | ❌ | ❌ |
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### How can I add a new library to the Inference API?
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