⚠️ 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    

Introduction Language models are becoming larger all the time. At the time of    

This blog post will show how easy it is to fine-tune pre-trained Transformer models for your dataset using the Hugging Face Optimum library on Graphcore Intelligence Processing Units (IPUs). As an example, we will show a step-by-step guide and provide a notebook that takes a large, widely-used chest X-ray dataset and trains a vision transformer (ViT) model. Introducing vision transformer (ViT)    

In the previous posts, we showed how to deploy a Vision Transformers (ViT) model from 🤗 Transformers locally and on a Kubernetes cluster. This post will show you    

In this Tutorial, you will learn how to pre-train BERT-base from scratch using a Habana Gaudi-based DL1 instance on AWS to take advantage of the cost-performance benefits of Gaudi. We will use the Hugging Face Transformers, Optimum Habana and Datasets libraries to pre-train a BERT-base model using masked-language modeling, one of the two original BERT pre-training    

Stable Diffusion 🎨 …using 🧨 Diffusers Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from CompVis, Stability AI and LAION. It is trained on 512×512 images from a subset of the LAION-5B database. LAION-5B is the largest, freely accessible multi-modal dataset that currently exists. In this post, we want to show how to use Stable Diffusion with the 🧨 Diffusers library, explain how the model works and finally dive a bit deeper into how […]