In this blog post, we will look at how to fine-tune Llama 2 70B using PyTorch FSDP and related best practices. We will be leveraging Hugging Face Transformers, Accelerate and TRL. We will also learn how to use Accelerate with SLURM. Fully Sharded Data Parallelism (FSDP) is a paradigm in which the optimizer states, gradients and parameters are sharded across devices. During the forward pass, each FSDP unit performs an all-gather operation to get the complete weights, computation is performed […]

What is Würstchen? Würstchen is a diffusion model, whose text-conditional component works in a highly compressed latent space of images. Why is this important? Compressing data can reduce computational costs for both training and inference by orders of magnitude. Training on 1024×1024 images is way more expensive than training on 32×32. Usually, other works make use of a relatively small compression, in the range of 4x – 8x    

Note: This blog post is also available as a documentation page on Transformers. Large Language Models (LLMs) such as GPT3/4, Falcon, and LLama are rapidly advancing in their ability to tackle human-centric tasks, establishing themselves as essential tools in modern knowledge-based industries. Deploying these models in real-world tasks remains    

Welcome to our latest dive into the world of leaderboards and models evaluation. In a previous post, we navigated the waters of evaluating Large Language Models. Today, we set sail to a different, yet equally challenging domain – Object Detection.    

3D Gaussian Splatting is a rasterization technique described in 3D Gaussian Splatting for Real-Time Radiance Field Rendering that allows real-time rendering of photorealistic scenes learned from small samples of images. This article will break down how it works and what it means for the future of graphics.

Today, we’re introducing Inference for PRO users – a community offering that gives you access to APIs of curated endpoints for some of the most exciting models available, as well as improved rate limits for the usage of free Inference API. Use the following page to subscribe to PRO. Hugging Face PRO users now have access to exclusive API endpoints for a curated list of powerful models that benefit from ultra-fast inference powered by text-generation-inference. This is a benefit on […]

Deploying large language models (LLMs) and other generative AI models can be challenging due to their computational requirements and latency needs. To provide useful recommendations to companies looking to deploy Llama 2 on Amazon SageMaker with the Hugging Face LLM Inference Container, we created a comprehensive benchmark analyzing over 60 different deployment configurations for Llama    

In this tutorial we will show you how anyone can build their own open-source ChatGPT without ever writing a single line of code! We’ll use the LLaMA 2 base model, fine tune it for chat with an open-source instruction    

Diffusion models (e.g., DALL-E 2, Stable Diffusion) are a class of generative models that are widely successful at generating images most notably of the photorealistic kind. However, the images generated by these models may not always be on par with human preference or human intention. Thus arises the alignment problem i.e. how does one go about making sure that the outputs of a model are aligned with human preferences like “quality” or that outputs are aligned with intent that is […]