| Library                                                                     | Description                                                                          | Inference Providers | Widgets | Download from Hub | Push to Hub |
|-----------------------------------------------------------------------------|--------------------------------------------------------------------------------------|---|---:|---|---|
| [Adapters](./adapters) | A unified Transformers add-on for parameter-efficient and modular fine-tuning.                                                | ✅  | ✅  | ✅ | ✅ |
| [AllenNLP](./allennlp)                             | An open-source NLP research library, built on PyTorch.                               | ✅ | ✅ | ✅ | ❌ |
| [Asteroid](./asteroid)                       | PyTorch-based audio source separation toolkit                                        | ✅ | ✅ | ✅ | ❌ |
| [BERTopic](./bertopic)                           | BERTopic is a topic modeling library for text and images                             | ✅ | ✅ | ✅ | ✅ | 
| [Diffusers](./diffusers)                       | A modular toolbox for inference and training of diffusion models                     | ✅ | ✅ | ✅ | ✅ |
| [docTR](https://github.com/mindee/doctr)                                    | Models and datasets for OCR-related tasks in PyTorch & TensorFlow                    | ✅ | ✅ | ✅ | ❌ |
| [ESPnet](./espnet)                                  | End-to-end speech processing toolkit (e.g. TTS)                                      | ✅ | ✅ | ✅ | ❌ |
| [fastai](./fastai)                                  | Library to train fast and accurate models with state-of-the-art outputs.             | ✅ | ✅ | ✅ | ✅ |
| [Keras](./keras)                              | Open-source multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. | ❌ | ❌ | ✅ | ✅ |
| [KerasNLP](https://keras.io/guides/keras_nlp/upload/)                              | Natural language processing library built on top of Keras that works natively with TensorFlow, JAX, or PyTorch. | ❌ | ❌ | ✅ | ✅ |
| [TF-Keras](./tf-keras) (legacy)                              | Legacy library that uses a consistent and simple API to build models leveraging TensorFlow and its ecosystem. | ❌ | ❌ | ✅ | ✅ |
| [Flair](./flair)                                  | Very simple framework for state-of-the-art NLP.                                      | ✅ | ✅ | ✅ | ✅ |
| [MBRL-Lib](https://github.com/facebookresearch/mbrl-lib)                    | PyTorch implementations of MBRL Algorithms.                                          | ❌ | ❌ | ✅ | ✅ |
| [MidiTok](https://github.com/Natooz/MidiTok)                                | Tokenizers for symbolic music / MIDI files.                                          | ❌ | ❌ | ✅ | ✅ |
| [ML-Agents](./ml-agents)                       | Enables games and simulations made with Unity to serve as environments for training intelligent agents. | ❌ | ❌ | ✅ | ✅ |
| [MLX](./mlx)                       | Model training and serving framework on Apple silicon made by Apple. | ❌ | ❌ | ✅ | ✅ |
| [NeMo](https://github.com/NVIDIA/NeMo)                                      | Conversational AI toolkit built for researchers                                      | ✅ | ✅ | ✅ | ❌ |
| [OpenCLIP](./open_clip)                      | Library for open-source implementation of OpenAI's CLIP                              | ❌ | ❌ | ✅ | ✅ |  
| [PaddleNLP](./paddlenlp)                      | Easy-to-use and powerful NLP library built on PaddlePaddle                           | ✅ | ✅ | ✅ | ✅ |
| [PEFT](./peft)                      | Cutting-edge Parameter Efficient Fine-tuning Library                           | ✅ | ✅ | ✅ | ✅ |
| [Pyannote](https://github.com/pyannote/pyannote-audio)                      | Neural building blocks for speaker diarization.                                      | ❌ | ❌ | ✅ | ❌ |
| [PyCTCDecode](https://github.com/kensho-technologies/pyctcdecode)           | Language model supported CTC decoding for speech recognition                         | ❌ | ❌ | ✅ | ❌ |
| [Pythae](https://github.com/clementchadebec/benchmark_VAE)                  | Unified framework for Generative Autoencoders in Python                              | ❌ | ❌ | ✅ | ✅ |
| [RL-Baselines3-Zoo](./rl-baselines3-zoo)            | Training framework for Reinforcement Learning, using [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3).| ❌ | ✅ | ✅ | ✅ |
| [Sample Factory](./sample-factory)           | Codebase for high throughput asynchronous reinforcement learning.                    | ❌ | ✅ | ✅ | ✅ |
| [Sentence Transformers](./sentence-transformers)    | Compute dense vector representations for sentences, paragraphs, and images.          | ✅ | ✅ | ✅ | ✅ |
| [SetFit](./setfit)                             | Efficient few-shot text classification with Sentence Transformers                    | ✅ | ✅ | ✅ | ✅ |
| [spaCy](./spacy)                                 | Advanced Natural Language Processing in Python and Cython.                           | ✅ | ✅ | ✅ | ✅ |
| [SpanMarker](./span_marker)                    | Familiar, simple and state-of-the-art Named Entity Recognition.                      | ✅ | ✅ | ✅ | ✅ |
| [Scikit Learn (using skops)](https://skops.readthedocs.io/en/stable/)       | Machine Learning in Python.                                                          | ✅ | ✅ | ✅ | ✅ |
| [Speechbrain](./speechbrain)                               | A PyTorch Powered Speech Toolkit.                                                    | ✅ | ✅ | ✅ | ❌ |
| [Stable-Baselines3](./stable-baselines3)            | Set of reliable implementations of deep reinforcement learning algorithms in PyTorch | ❌ | ✅ | ✅ | ✅ |
| [TensorFlowTTS](https://github.com/TensorSpeech/TensorFlowTTS)              | Real-time state-of-the-art speech synthesis architectures.                           | ❌ | ❌ | ✅ | ❌ |
| [Timm](./timm)                   | Collection of image models, scripts, pretrained weights, etc.                        | ✅ | ✅ | ✅ | ✅ |
| [Transformers](./transformers)                 | State-of-the-art Natural Language Processing for PyTorch, TensorFlow, and JAX        | ✅ | ✅ | ✅ | ✅ |
| [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! | ❌ | ❌ | ✅ | ❌ |
| [Unity Sentis](./unity-sentis)                | Inference engine for the Unity 3D game engine | ❌ | ❌ | ❌ | ❌ |