🌍Integrated Libraries

Libraries

The Hub has support for dozens of libraries in the Open Source ecosystem. Thanks to the boincai_hub Python library, it’s easy to enable sharing your models on the Hub. The Hub supports many libraries, and we’re working on expanding this support! We’re happy to welcome to the Hub a set of Open Source libraries that are pushing Machine Learning forward.

The table below summarizes the supported libraries and their level of integration. Find all our supported libraries here!

Library	Description	Inference API	Widgets	Download from Hub	Push to Hub
Adapter Transformers	Extends 🌍Transformers with Adapters.	❌	❌	✅	✅
AllenNLP	An open-source NLP research library, built on PyTorch.	✅	✅	✅	❌
Asteroid	Pytorch-based audio source separation toolkit	✅	✅	✅	❌
BERTopic	BERTopic is a topic modeling library for text and images	✅	✅	✅	✅
Diffusers	A modular toolbox for inference and training of diffusion models	✅	✅	✅	✅
docTR	Models and datasets for OCR-related tasks in PyTorch & TensorFlow	✅	✅	✅	❌
ESPnet	End-to-end speech processing toolkit (e.g. TTS)	✅	✅	✅	❌
fastai	Library to train fast and accurate models with state-of-the-art outputs.	✅	✅	✅	✅
Keras	Library that uses a consistent and simple API to build models leveraging TensorFlow and its ecosystem.	❌	❌	✅	✅
Flair	Very simple framework for state-of-the-art NLP.	✅	✅	✅	✅
MBRL-Lib	PyTorch implementations of MBRL Algorithms.	❌	❌	✅	✅
MidiTok	Tokenizers for symbolic music / MIDI files.	❌	❌	✅	✅
ML-Agents	Enables games and simulations made with Unity to serve as environments for training intelligent agents.	❌	❌	✅	✅
NeMo	Conversational AI toolkit built for researchers	✅	✅	✅	❌
PaddleNLP	Easy-to-use and powerful NLP library built on PaddlePaddle	✅	✅	✅	✅
Pyannote	Neural building blocks for speaker diarization.	❌	❌	✅	❌
PyCTCDecode	Language model supported CTC decoding for speech recognition	❌	❌	✅	❌
Pythae	Unified framework for Generative Autoencoders in Python	❌	❌	✅	✅
RL-Baselines3-Zoo	Training framework for Reinforcement Learning, using Stable Baselines3.	❌	✅	✅	✅
Sample Factory	Codebase for high throughput asynchronous reinforcement learning.	❌	✅	✅	✅
Sentence Transformers	Compute dense vector representations for sentences, paragraphs, and images.	✅	✅	✅	✅
spaCy	Advanced Natural Language Processing in Python and Cython.	✅	✅	✅	✅
SpanMarker	Familiar, simple and state-of-the-art Named Entity Recognition.	✅	✅	✅	✅
Scikit Learn (using skops)	Machine Learning in Python.	✅	✅	✅	✅
Speechbrain	A PyTorch Powered Speech Toolkit.	✅	✅	✅	❌
Stable-Baselines3	Set of reliable implementations of deep reinforcement learning algorithms in PyTorch	❌	✅	✅	✅
TensorFlowTTS	Real-time state-of-the-art speech synthesis architectures.	❌	❌	✅	❌
Timm	Collection of image models, scripts, pretrained weights, etc.	✅	✅	✅	✅
Transformers	State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX	✅	✅	✅	✅
Transformers.js	State-of-the-art Machine Learning for the web. Run 🌍 Transformers directly in your browser, with no need for a server!	❌	❌	✅	❌

How can I add a new library to the Inference API?

If you’re interested in adding your library, please reach out to us! Read about it in Adding a Library Guide.