OpenAI Jukebox
Search results
Give your team the most advanced platform to build AI with enterprise-grade security, access controls and dedicated support. Getting started. Starting at $20/user/month. Single Sign-On Regions Priority Support Audit Logs Resource Groups Private Datasets Viewer. More than 50,000 organizations are using Hugging Face. Ai2. non-profit • 333 models.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Create a new model. From the website. Hub documentation. Take a first look at the Hub features. Programmatic access. Use the Hub’s Python client library
The AI community building the future. Hugging Face has 255 repositories available. Follow their code on GitHub.
Transformers is more than a toolkit to use pretrained models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable developers, researchers, students, professors, engineers, and anyone else to build their dream projects.
Revenue. 15,000,000 United States dollar (2022) Number of employees. 170 (2023) Website. huggingface.co. Hugging Face, Inc. is an American company incorporated under the Delaware General Corporation Law [1] and based in New York City that develops computation tools for building applications using machine learning.
The course teaches you about applying Transformers to various tasks in natural language processing and beyond. Along the way, you'll learn how to use the Hugging Face ecosystem — 🤗 Transformers, 🤗 Datasets, 🤗 Tokenizers, and 🤗 Accelerate — as well as the Hugging Face Hub. It's completely free and open-source!
Explore HuggingFace's YouTube channel for tutorials and insights on Natural Language Processing, open-source contributions, and scientific advancements.
To solve this problem Matthew Carrigan from the Hugging Face team introduced "chat template". It is a Jinja template (for each model) that solves the problems of formatting the propmt correctly ...
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX. 🤗 Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch.
