Hugging Face
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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.
- 🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
pytorch-image-models
PublicThe 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 moredoc-builder
Public- 🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
- The official Python client for the Hugging Face Hub.
- 🤗 Optimum Intel: Accelerate inference with Intel optimization tools
hub-docs
PublicDocs of the Hugging Face Hub- Easy and lightning fast training of 🤗 Transformers on Habana Gaudi processor (HPU)
- Use Hugging Face with JavaScript
- 🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
- Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
- Backend that powers the dataset viewer on Hugging Face dataset pages through a public API.
- 🔥The Web-scale GUI for MongoDB
- Public repo for HF blog posts