Kronos is an open-source decoder-only foundation model pretrained on financial candlestick (K-line) sequences for market forecasting.
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
π€ 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.
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Chronos: Pretrained Models for Time Series Forecasting
REKI: a 2.4B vision-language-action model pretrained on public data only, with a memory of its recent past at negligible cost.
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
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
The official CLI and Python client for the Hugging Face Hub.
An open source implementation of CLIP.
Tools for merging pretrained large language models.
TimeGPT-2.1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code π.
Toolkit to segment text into sentences or other semantic units in a robust, efficient and adaptable way.
Shared Ultralytics logos, media, sample images, pretrained model weights, dataset artifacts, and release assets.
A collection of pre-trained, state-of-the-art models in the ONNX format
Silero Models: pre-trained text-to-speech models made embarrassingly simple
A treasure chest for visual classification and recognition powered by PaddlePaddle
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
The PyTorch-based audio source separation toolkit for researchers
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
Pretrained model hub for Keras 3.
[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
Official Codebase for "Neural Thickets: Diverse Task Experts Are Dense Around Pretrained Weights" (ICML 2026 Spotlight)
Discover pretrained models for deep learning in MATLAB
PyTorch Lightning Optical Flow models, scripts, and pretrained weights.
A pretrained tabular foundation model for classification and regression by Nums AI Inc.
Pretrained text classifiers you can run and retrain on CPU
Paper: training keyframe-animation adapters on a pretrained video model.
Domain Adaptation with BERT and Hugging Face: 2026 Guide to Fine-Tuning Pretrained Models
LightVAE: Fast video VAE decoders for Wan2.1, Wan2.2, and MiniMax-H3, plus a compressed H3 reference encoder. Pretrained weights and ComfyUI workflows.