awesome-huggingface
This is a list of some wonderful open-source projects & applications integrated with Hugging Face libraries.
🤗 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 huggingface.co hub.
- tune - A benchmark for comparing Transformer-based models.
👩🏫 Tutorials
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.
🗺 Translation
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
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.
🤯 Multi-modality
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.
⚖️ Evaluation
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
Cloud makes your life easy!
- Amazon SageMaker - Making it easier than ever to train Hugging Face Transformer models in Amazon SageMaker.
📱 Hardware
The infrastructure enabling the magic to happen.