Awesome Huggingface

🤗 A list of wonderful open-source projects & applications integrated with Hugging Face libraries.
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This is a list of some wonderful open-source projects & applications integrated with Hugging Face libraries.

How to contribute

Official Libraries

First-party cool stuff made with by Hugging Face.

  • transformers - State-of-the-art natural language processing for Jax, PyTorch and TensorFlow.
  • datasets - The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools.
  • tokenizers - Fast state-of-the-Art tokenizers optimized for research and production.
  • knockknock - Get notified when your training ends with only two additional lines of code.
  • accelerate - A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision.
  • autonlp - Train state-of-the-art natural language processing models and deploy them in a scalable environment automatically.
  • nn_pruning - Prune a model while finetuning or training.
  • huggingface_hub - Client library to download and publish models and other files on the hub.
  • tune - A benchmark for comparing Transformer-based models.


Learn how to use Hugging Face toolkits, step-by-step.

  • Official Course (from Hugging Face) - The official course series provided by Hugging Face.
  • transformers-tutorials (by @nielsrogge) - Tutorials for applying multiple models on real-world datasets.

NLP Toolkits

NLP toolkits built upon Transformers. Swiss Army!

  • AllenNLP (from AI2) - An open-source NLP research library.
  • Graph4NLP - Enabling easy use of Graph Neural Networks for NLP.
  • Lightning Transformers - Transformers with PyTorch Lightning interface.
  • Adapter Transformers - Extension to the Transformers library, integrating adapters into state-of-the-art language models.
  • Obsei - A low-code AI workflow automation tool and performs various NLP tasks in the workflow pipeline.
  • Trapper (from OBSS) - State-of-the-art NLP through transformer models in a modular design and consistent APIs.

Text Representation

Converting a sentence to a vector.

  • Sentence Transformers (from UKPLab) - Widely used encoders computing dense vector representations for sentences, paragraphs, and images.
  • WhiteningBERT (from Microsoft) - An easy unsupervised sentence embedding approach with whitening.
  • SimCSE (from Princeton) - State-of-the-art sentence embedding with contrastive learning.
  • DensePhrases (from Princeton) - Learning dense representations of phrases at scale.

Inference Engines

Highly optimized inference engines implementing Transformers-compatible APIs.

  • TurboTransformers (from Tencent) - An inference engine for transformers with fast C++ API.
  • FasterTransformer (from Nvidia) - A script and recipe to run the highly optimized transformer-based encoder and decoder component on NVIDIA GPUs.
  • lightseq (from ByteDance) - A high performance inference library for sequence processing and generation implemented in CUDA.
  • FastSeq (from Microsoft) - Efficient implementation of popular sequence models (e.g., Bart, ProphetNet) for text generation, summarization, translation tasks etc.

Model Scalability

Parallelization models across multiple GPUs.

  • Parallelformers (from TUNiB) - A library for model parallel deployment.
  • OSLO (from TUNiB) - A library that supports various features to help you train large-scale models.
  • Deepspeed (from Microsoft) - Deepspeed-ZeRO - scales any model size with zero to no changes to the model. Integrated with HF Trainer.
  • fairscale (from Facebook) - Implements ZeRO protocol as well. Integrated with HF Trainer.
  • ColossalAI (from Hpcaitech) - A Unified Deep Learning System for Large-Scale Parallel Training (1D, 2D, 2.5D, 3D and sequence parallelism, and ZeRO protocol).

Model Compression/Acceleration

Compressing or accelerate models for improved inference speed.

  • torchdistill - PyTorch-based modular, configuration-driven framework for knowledge distillation.
  • TextBrewer (from HFL) - State-of-the-art distillation methods to compress language models.
  • BERT-of-Theseus (from Microsoft) - Compressing BERT by progressively replacing the components of the original BERT.

Adversarial Attack

Conducting adversarial attack to test model robustness.

  • TextAttack (from UVa) - A Python framework for adversarial attacks, data augmentation, and model training in NLP.
  • TextFlint (from Fudan) - A unified multilingual robustness evaluation toolkit for NLP.
  • OpenAttack (from THU) - An open-source textual adversarial attack toolkit.

Style Transfer

Transfer the style of text! Now you know why it's called transformer?

  • Styleformer - A neural language style transfer framework to transfer text smoothly between styles.
  • ConSERT - A contrastive framework for self-supervised sentence representation transfer.

Sentiment Analysis

Analyzing the sentiment and emotions of human beings.

  • conv-emotion - Implementation of different architectures for emotion recognition in conversations.

Grammatical Error Correction

You made a typo! Let me correct it.

  • Gramformer - A framework for detecting, highlighting and correcting grammatical errors on natural language text.


Translating between different languages.

  • dl-translate - A deep learning-based translation library based on HF Transformers.
  • EasyNMT (from UKPLab) - Easy-to-use, state-of-the-art translation library and Docker images based on HF Transformers.

Knowledge and Entity

Learning knowledge, mining entities, connecting the world.

  • PURE (from Princeton) - Entity and relation extraction from text.


Speech processing powered by HF libraries. Need for speech!

  • s3prl - A self-supervised speech pre-training and representation learning toolkit.
  • speechbrain - A PyTorch-based speech toolkit.


Understanding the world from different modalities.

  • ViLT (from Kakao) - A vision-and-language transformer Without convolution or region supervision.

Reinforcement Learning

Combining RL magic with NLP!

  • trl - Fine-tune transformers using Proximal Policy Optimization (PPO) to align with human preferences.

Question Answering

Searching for answers? Transformers to the rescue!

  • Haystack (from deepset) - End-to-end framework for developing and deploying question-answering systems in the wild.

Recommender Systems

I think this is just right for you!

  • Transformers4Rec (from Nvidia) - A flexible and efficient library powered by Transformers for sequential and session-based recommendations.


Evaluating NLP outputs powered by HF datasets!

  • Jury (from OBSS) - Easy to use tool for evaluating NLP model outputs, spesifically for NLG (Natural Language Generation), offering various automated text-to-text metrics.

Neural Search

Search, but with the power of neural networks!

  • Jina Integration - Jina integration of Hugging Face Accelerated API.
  • Weaviate Integration (text2vec) (QA) - Weaviate integration of Hugging Face Transformers.
  • ColBERT (from Stanford) - A fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds.


Cloud makes your life easy!

  • Amazon SageMaker - Making it easier than ever to train Hugging Face Transformer models in Amazon SageMaker.


The infrastructure enabling the magic to happen.

  • Qualcomm - Collaboration on enabling Transformers in Snapdragon.
  • Intel - Collaboration with Intel for configuration options.
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