🤗 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 official Python client for the Hugging Face Hub.

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.

mindspore implementation of transformers

[ICLR2024] Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How

Neural Nexus : A comprehensive AI model hub for uploading , sharing, selling, and deploying machine learning models. Features Secure authentication, Stripe/Crypto Payments, model ownership transfer via blockchain, and a vibrant community. Build with Next.js, Tailwind CSS, React, and Framer Motion

Code to generate the PTMTorrent dataset

golang client for the huggingface hub aiming for minimal subset of features over `huggingface-hub` python package

Deep Learning models for JavaScript.

State-of-the-art Machine Learning for Dart. Run 🤗 Transformers cross-platform on your device, with no need for a server!

An unofficial C++ client for the Huggingface Hub

Website for the Ersilia Model Hub

A simple, portable library to interact with the 🤗 Hub & Inference APIs!

🤖 Run state-of-the-art Machine Learning models in Dart with transformers_dart—cross-platform, serverless, and based on Hugging Face's transformers.

🔍 Monitor transformer health in real time using ESP32 to detect faults via temperature and current sensors, ensuring timely alerts and failure prevention

The unofficial Dart client for the Huggingface Hub.