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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
- Backend that powers the dataset viewer on Hugging Face dataset pages through a public API.
- 🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
- AI Energy Score: Initiative to establish comparable energy efficiency ratings for AI models.
- 🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
- Open source codebase powering the HuggingChat app
- 🤗 Optimum Intel: Accelerate inference with Intel optimization tools
- The official Python client for the Hugging Face Hub.
- A blazing fast inference solution for text embeddings models
- 🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
- Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
- Use Hugging Face with JavaScript