TL;DR: Text Generation on 🤗 transformers using TensorFlow can now be compiled with XLA. It is up to 100x faster than before, and even faster than PyTorch — check the colab below! Text Generation    

In late June 2022, Hugging Face submitted a response to the White House Office of Science and Technology Policy and National Science Foundation’s Request for Information on a roadmap for implementing the National Artificial Intelligence Research Resource (NAIRR) Task Force’s interim report findings. As a platform working to democratize machine learning by empowering all backgrounds to contribute to AI, we strongly    

June 2023 Update: The Private Hub is now called Enterprise Hub. The Enterprise Hub is a hosted solution that combines the best of Cloud Managed services (SaaS) and Enterprise security. It lets customers deploy specific services like Inference Endpoints on a wide scope of compute options, from on-cloud to on-prem. It offers advanced user administration and access controls through    

⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introduction This article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here. ⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introduction This article is part of the Deep Reinforcement Learning    

This guide is only suited for Sentence Transformers before v3.0. Read Training and Finetuning Embedding Models with Sentence Transformers v3 for an updated guide. Check out this tutorial with the Notebook Companion: Training or fine-tuning a Sentence Transformers model highly depends on the available data and the target task. The    

Introduction Despite increasing competition from PyTorch and JAX, TensorFlow remains the most-used deep learning framework. It also differs from those other two libraries in some very important ways. In particular, it’s quite tightly integrated with its high-level API Keras,    

At Hugging Face, we are working on tackling various problems in open-source machine learning, including, hosting