huggingface/transformers
🤗 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.
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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.
An open source implementation of CLIP.
Chronos: Pretrained Models for Time Series Forecasting
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
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
The official CLI and Python client for the Hugging Face Hub.
The PyTorch-based audio source separation toolkit for researchers
PyTorch Lightning Optical Flow models, scripts, and pretrained weights.
Toolkit to segment text into sentences or other semantic units in a robust, efficient and adaptable way.
Pretrained text classifiers you can run and retrain on CPU
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
That's all 12 repositories in this period.