🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
🤗 smolagents: a barebones library for agents that think in code.
🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning
Fully open reproduction of DeepSeek-R1
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Train transformer language models with reinforcement learning.
State-of-the-Art Embeddings, Retrieval, and Reranking
A PyTorch-based Speech Toolkit
Give your agents the power of the Hugging Face ecosystem
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.
Plan and train German transformer models.
A minimalistic codebase for training NLG models from HuggingFace Transformers using PyTorch Lightning.