PinnedNext public talksHere’s the current list of public events I’ll be speaking at. I will keep it as up-to-date as possible! I’m always open to speaking at public events (online or in-person). I’m also happy to explore opportunities for in-house talks. Don’t hesitate to get in touch with details at julsimon@huggingface.co. September-November…3 min read3 min read
Nov 2Retrieval Augmented Chatbot, part 2! LangChain, Hugging Face, Amazon SageMaker, and Amazon OpenSearch Serverless 😀We start by deploying Mistral 7B, a cutting-edge open-source LLM, onto a SageMaker endpoint. Following this, we work with the Reuters dataset, a Hugging Face dataset comprising 20,000 news articles. We break down these articles into smaller sections and apply bge-small, a compact open-source embedding model, to them. Next, we…AWS1 min readAWS1 min read
Oct 24Building a Retrieval-Augmented Generation (RAG) Chatbot with LangChain, Hugging Face, and AWSSIn this video, I’ll guide you through the process of creating a Retrieval-Augmented Generation (RAG) chatbot using open-source tools and AWS services, such as LangChain, Hugging Face, FAISS, Amazon SageMaker, and Amazon TextTract. We begin by working with PDF files in the Energy domain. Our first step involves leveraging…AWS1 min readAWS1 min read
Oct 18Maximize Hugging Face training efficiency with QLoRAIn this video, I delve into optimizing the fine-tuning of a Google FLAN-T5 model for legal text summarization. The focus is on employing QLoRA for parameter-efficient fine-tuning: all it takes is a few extra lines of simple code in your existing script. This methodology allows us to train the model…AWS1 min readAWS1 min read
Oct 10For a fistful of dollars: fine-tune LLaMA 2 7B with QLoRAFine-tuning large language models doesn’t have to be complicated and expensive. In this tutorial, I provide a step-by-step demonstration of the fine-tuning process for a LLaMA 2 7-billion parameter model. Thanks to LoRA, 4-bit quantization and a modest AWS GPU instance (g5.xlarge), total cost is just a fistful of dollars…AWS1 min readAWS1 min read
Oct 9Fine-tune Stable Diffusion with LoRA for as low as $1Fine-tuning large models doesn’t have to be complicated and expensive. In this tutorial, I provide a step-by-step demonstration of the fine-tuning process for a Stable Diffusion model geared towards Pokemon image generation. Utilizing a pre-existing script sourced from the Hugging Face diffusers library, the configuration is set to leverage the…AWS1 min readAWS1 min read
Oct 8Azure ML: start experimenting with Hugging Face models in minutes!In this video, I show you how to deploy Hugging Face models in one click on Azure, thanks to the model catalog in Azure ML Studio. Then, I run a small Python example to predict with the model. To get started, you simply need to navigate to the Azure…Azure1 min readAzure1 min read
Oct 8SageMaker JumpStart: start experimenting with large language models in minutes!Experimenting with the latest and greatest models doesn’t have to be difficult. With SageMaker JumpStart, you can easily access and experiment with cutting-edge large language models without the hassle of setting up complex infrastructure or writing deployment code. All it takes is a single click. In this particular video, I…AWS1 min readAWS1 min read
Sep 15Accelerating Stable Diffusion with Optimum Neuron and AWS Inferentia2In this video, I show you how to accelerate Stable Diffusion and Stable Diffusion XL inference with the Hugging Face Optimum Neuron library and AWS Inferentia 2. A few lines of code is all it takes, and of course, we run some benchmarks.Hugging Face1 min readHugging Face1 min read
May 17Video: Transformer training shootout, part 2: AWS Trainium vs. NVIDIA V100In this video, I compare the cost/performance of AWS Trainium with the NVIDIA V100 GPU. I first launch a trn1.32xlarge instance (16 Trainium chips) and a p3dn.24xlarge (8 V100s). Then, I run 3 benchmarks: language pretraining with GPT2, token classification with BERT Large, and image classification with the Vision Transformer. …Deep Learning1 min readDeep Learning1 min read
