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VOOZH | about |
🤗 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
golang client for the huggingface hub aiming for minimal subset of features over `huggingface-hub` python package
AI-powered crypto trading signals verified in OpenGradient TEE. 6 technical indicators + LLM macro-risk verdict + ONNX volatility forecast. Next.js 16 · React 19 · TypeScript · Tailwind CSS 4 · Binance API · onnxruntime
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
A simple, portable library to interact with the 🤗 Hub & Inference APIs!
An open-source model and dataset Hub with LFS support backed by Xet, fully compatible with 🤗 Libraries.
Capture and translate live speech with GPU-free Vosk, AI refinement, and Google fallback for stable bilingual transcripts
🤖 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
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