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https://huggingface.co/blog/blip-2 | Zero-shot image-to-text generation with BLIP-2 | Maria Khalusova, JunnanLi | February 15, 2023 | This guide introduces BLIP-2 from Salesforce Research that enables a suite of state-of-the-art visual-language models that are now available in 🤗 Transformers. We'll show you how to use it for image captioning, prompted image captioning, visual question-answering, and chat-based prompting. Table of contents Introduct... |
https://huggingface.co/blog/mantis-case-study | Why we’re switching to Hugging Face Inference Endpoints, and maybe you should too | Matthew Upson | February 15, 2023 | Hugging Face recently launched Inference Endpoints; which as they put it: solves transformers in production. Inference Endpoints is a managed service that allows you to:Deploy (almost) any model on Hugging Face HubTo any cloud (AWS, and Azure, GCP on the way)On a range of instance types (including GPU)We’re switching s... |
https://huggingface.co/blog/peft | 🤗 PEFT: Parameter-Efficient Fine-Tuning of Billion-Scale Models on Low-Resource Hardware | Sourab Mangrulkar, Sayak Paul | February 10, 2023 | Motivation Large Language Models (LLMs) based on the transformer architecture, like GPT, T5, and BERT have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. They have also started foraying into other domains, such as Computer Vision (CV) (VIT, Stable Diffusion, LayoutLM) and Audio (W... |
https://huggingface.co/blog/speecht5 | Speech Synthesis, Recognition, and More With SpeechT5 | Matthijs Hollemans | February 8, 2023 | We’re happy to announce that SpeechT5 is now available in 🤗 Transformers, an open-source library that offers easy-to-use implementations of state-of-the-art machine learning models.SpeechT5 was originally described in the paper SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing by Micr... |
https://huggingface.co/blog/ml-for-games-5 | Generating Stories: AI for Game Development #5 | Dylan Ebert | February 7, 2023 | Welcome to AI for Game Development! In this series, we'll be using AI tools to create a fully functional farming game in just 5 days. By the end of this series, you will have learned how you can incorporate a variety of AI tools into your game development workflow. I will show you how you can use AI tools for:Art Style... |
https://huggingface.co/blog/aivsai | Introducing ⚔️ AI vs. AI ⚔️ a deep reinforcement learning multi-agents competition system | Carl Cochet, Thomas Simonini | February 7, 2023 | We’re excited to introduce a new tool we created: ⚔️ AI vs. AI ⚔️, a deep reinforcement learning multi-agents competition system.This tool, hosted on Spaces, allows us to create multi-agent competitions. It is composed of three elements:A Space with a matchmaking algorithm that runs the model fights using a background ... |
https://huggingface.co/blog/intel-sapphire-rapids-inference | Accelerating PyTorch Transformers with Intel Sapphire Rapids, part 2 | Julien Simon | February 6, 2023 | In a recent post, we introduced you to the fourth generation of Intel Xeon CPUs, code-named Sapphire Rapids, and its new Advanced Matrix Extensions (AMX) instruction set. Combining a cluster of Sapphire Rapids servers running on Amazon EC2 and Intel libraries like the Intel Extension for PyTorch, we showed you how to e... |
https://huggingface.co/blog/vision_language_pretraining | A Dive into Vision-Language Models | Alara Dirik, Sayak Paul | February 3, 2023 | Human learning is inherently multi-modal as jointly leveraging multiple senses helps us understand and analyze new information better. Unsurprisingly, recent advances in multi-modal learning take inspiration from the effectiveness of this process to create models that can process and link information using various moda... |
https://huggingface.co/blog/cv_state | The State of Computer Vision at Hugging Face 🤗 | Sayak Paul | January 30, 2023 | At Hugging Face, we pride ourselves on democratizing the field of artificial intelligence together with the community. As a part of that mission, we began focusing our efforts on computer vision over the last year. What started as a PR for having Vision Transformers (ViT) in 🤗 Transformers has now grown into something... |
https://huggingface.co/blog/ml-for-games-4 | 2D Asset Generation: AI for Game Development #4 | Dylan Ebert | January 26, 2023 | Welcome to AI for Game Development! In this series, we'll be using AI tools to create a fully functional farming game in just 5 days. By the end of this series, you will have learned how you can incorporate a variety of AI tools into your game development workflow. I will show you how you can use AI tools for:Art Style... |
https://huggingface.co/blog/lora | Using LoRA for Efficient Stable Diffusion Fine-Tuning | Pedro Cuenca, Sayak Paul | January 26, 2023 | LoRA: Low-Rank Adaptation of Large Language Models is a novel technique introduced by Microsoft researchers to deal with the problem of fine-tuning large-language models. Powerful models with billions of parameters, such as GPT-3, are prohibitively expensive to fine-tune in order to adapt them to particular tasks or do... |
https://huggingface.co/blog/dialog-agents | What Makes a Dialog Agent Useful? | Nazneen Rajani, Nathan Lambert, Victor Sanh, Thomas Wolf | January 24, 2023 | The techniques behind ChatGPT: RLHF, IFT, CoT, Red teaming, and moreThis article has been translated to Chinese 简体中文. A few weeks ago, ChatGPT emerged and launched the public discourse into a set of obscure acronyms: RLHF, SFT, IFT, CoT, and more, all attributed to the success of ChatGPT. What are these obscure acronym... |
https://huggingface.co/blog/optimum-onnxruntime-training | Optimum + ONNX Runtime: Easier, Faster training for your Hugging Face models | Jingya Huang, Kshama Pawar, Ashwini Khade, Vincent Wang, zhijiang xu | January 24, 2023 | IntroductionTransformer based models in language, vision and speech are getting larger to support complex multi-modal use cases for the end customer. Increasing model sizes directly impact the resources needed to train these models and scale them as the size increases. Hugging Face and Microsoft’s ONNX Runtime teams ar... |
https://huggingface.co/blog/ml-for-games-3 | 3D Asset Generation: AI for Game Development #3 | Dylan Ebert | January 20, 2023 | Welcome to AI for Game Development! In this series, we'll be using AI tools to create a fully functional farming game in just 5 days. By the end of this series, you will have learned how you can incorporate a variety of AI tools into your game development workflow. I will show you how you can use AI tools for:Art Style... |
https://huggingface.co/blog/mask2former | Universal Image Segmentation with Mask2Former and OneFormer | Niels Rogge, Shivalika Singh, Alara Dirik | January 19, 2023 | This guide introduces Mask2Former and OneFormer, 2 state-of-the-art neural networks for image segmentation. The models are now available in 🤗 transformers, an open-source library that offers easy-to-use implementations of state-of-the-art models. Along the way, you'll learn about the difference between the various for... |
https://huggingface.co/blog/paddlepaddle | Welcome PaddlePaddle to the Hugging Face Hub | PaddlePaddle | January 17, 2023 | We are happy to share an open source collaboration between Hugging Face and PaddlePaddle on a shared mission to advance and democratize AI through open source!First open sourced by Baidu in 2016, PaddlePaddle enables developers of all skill levels to adopt and implement Deep Learning at scale. As of Q4 2022, PaddlePadd... |
https://huggingface.co/blog/image-similarity | Image Similarity with Hugging Face Datasets and Transformers | Sayak Paul | January 16, 2023 | In this post, you'll learn to build an image similarity system with 🤗 Transformers. Finding out the similarity between a query image and potential candidates is an important use case for information retrieval systems, such as reverse image search, for example. All the system is trying to answer is that, given a query ... |
https://huggingface.co/blog/ml-for-games-2 | AI for Game Development: Creating a Farming Game in 5 Days. Part 2 | Dylan Ebert | January 9, 2023 | Welcome to AI for Game Development! In this series, we'll be using AI tools to create a fully functional farming game in just 5 days. By the end of this series, you will have learned how you can incorporate a variety of AI tools into your game development workflow. I will show you how you can use AI tools for:Art Style... |
https://huggingface.co/blog/intro-graphml | Introduction to Graph Machine Learning | Clémentine Fourrier | January 3, 2023 | In this blog post, we cover the basics of graph machine learning. We first study what graphs are, why they are used, and how best to represent them. We then cover briefly how people learn on graphs, from pre-neural methods (exploring graph features at the same time) to what are commonly called Graph Neural Networks. La... |
https://huggingface.co/blog/ml-for-games-1 | AI for Game Development: Creating a Farming Game in 5 Days. Part 1 | Dylan Ebert | January 2, 2023 | Welcome to AI for Game Development! In this series, we'll be using AI tools to create a fully functional farming game in just 5 days. By the end of this series, you will have learned how you can incorporate a variety of AI tools into your game development workflow. I will show you how you can use AI tools for:Art Style... |
https://huggingface.co/blog/intel-sapphire-rapids | Accelerating PyTorch Transformers with Intel Sapphire Rapids, part 1 | Julien Simon | January 2, 2023 | About a year ago, we showed you how to distribute the training of Hugging Face transformers on a cluster or third-generation Intel Xeon Scalable CPUs (aka Ice Lake). Recently, Intel has launched the fourth generation of Xeon CPUs, code-named Sapphire Rapids, with exciting new instructions that speed up operations commo... |
https://huggingface.co/blog/clipseg-zero-shot | Zero-shot image segmentation with CLIPSeg | Tobias Cornille, Niels Rogge | December 21, 2022 | This guide shows how you can use CLIPSeg, a zero-shot image segmentation model, using 🤗 transformers. CLIPSeg creates rough segmentation masks that can be used for robot perception, image inpainting, and many other tasks. If you need more precise segmentation masks, we’ll show how you can refine the results of CLIPSeg... |
https://huggingface.co/blog/model-cards | Model Cards | Ezi Ozoani, Marissa Gerchick, Margaret Mitchell | December 20, 2022 | Introduction Model cards are an important documentation framework for understanding, sharing, and improving machine learning models. When done well, a model card can serve as a boundary object, a single artefact that is accessible to people with different backgrounds and goals in understanding models - including develo... |
https://huggingface.co/blog/ethics-soc-2 | Machine Learning in development: Let's talk about bias! | Yacine Jernite | December 15, 2022 | Bias in ML is ubiquitous, and Bias in ML is complex; so complex in fact that no single technical intervention is likely to meaningfully address the problems it engenders. ML models, as sociotechnical systems, amplify social trends that may exacerbate inequities and harmful biases in ways that depend on their deployment... |
https://huggingface.co/blog/audio-datasets | A Complete Guide to Audio Datasets | Sanchit Gandhi | December 15, 2022 | Introduction 🤗 Datasets is an open-source library for downloading and preparing datasets from all domains. Its minimalistic API allows users to download and prepare datasets in just one line of Python code, with a suite of functions that enable efficient pre-processing. The number of datasets available is unparalleled... |
https://huggingface.co/blog/habana-gaudi-2-benchmark | Faster Training and Inference: Habana Gaudi®-2 vs Nvidia A100 80GB | Régis Pierrard | December 14, 2022 | In this article, you will learn how to use Habana® Gaudi®2 to accelerate model training and inference, and train bigger models with 🤗 Optimum Habana. Then, we present several benchmarks including BERT pre-training, Stable Diffusion inference and T5-3B fine-tuning, to assess the performance differences between first ge... |
https://huggingface.co/blog/rlhf | Illustrating Reinforcement Learning from Human Feedback (RLHF) | Nathan Lambert, Louis Castricato, Leandro von Werra, Alex Havrilla | December 9, 2022 | This article has been translated to Chinese 简体中文 and Vietnamese đọc tiếng việt. Language models have shown impressive capabilities in the past few years by generating diverse and compelling text from human input prompts. However, what makes a "good" text is inherently hard to define as it is subjective and context depe... |
https://huggingface.co/blog/elixir-bumblebee | From GPT2 to Stable Diffusion: Hugging Face arrives to the Elixir community | José Valim | December 9, 2022 | The Elixir community is glad to announce the arrival of several Neural Networks models, from GPT2 to Stable Diffusion, to Elixir. This is possible thanks to the just announced Bumblebee library, which is an implementation of Hugging Face Transformers in pure Elixir.To help anyone get started with those models, the team... |
https://huggingface.co/blog/deep-learning-with-proteins | Deep Learning With Proteins | Matthew Carrigan | December 2, 2022 | I have two audiences in mind while writing this. One is biologists who are trying to get into machine learning, and the other is machine learners who are trying to get into biology. If you’re not familiar with either biology or machine learning then you’re still welcome to come along, but you might find it a bit confus... |
https://huggingface.co/blog/diffusers-coreml | Using Stable Diffusion with Core ML on Apple Silicon | Pedro Cuenca | December 1, 2022 | Thanks to Apple engineers, you can now run Stable Diffusion on Apple Silicon using Core ML!This Apple repo provides conversion scripts and inference code based on 🧨 Diffusers, and we love it! To make it as easy as possible for you, we converted the weights ourselves and put the Core ML versions of the models in the Hu... |
https://huggingface.co/blog/time-series-transformers | Probabilistic Time Series Forecasting with 🤗 Transformers | Niels Rogge, Kashif Rasul | December 1, 2022 | Introduction Time series forecasting is an essential scientific and business problem and as such has also seen a lot of innovation recently with the use of deep learning based models in addition to the classical methods. An important difference between classical methods like ARIMA and novel deep learning methods is the... |
https://huggingface.co/blog/vq-diffusion | VQ-Diffusion | Will Berman | November 30, 2022 | Vector Quantized Diffusion (VQ-Diffusion) is a conditional latent diffusion model developed by the University of Science and Technology of China and Microsoft. Unlike most commonly studied diffusion models, VQ-Diffusion's noising and denoising processes operate on a quantized latent space, i.e., the latent space is com... |
https://huggingface.co/blog/interns-2023 | We are hiring interns! | Lysandre, Douwe Kiela | November 29, 2022 | Want to help build the future at -- if we may say so ourselves -- one of the coolest places in AI? Today we’re announcing our internship program for 2023. Together with your Hugging Face mentor(s), we’ll be working on cutting edge problems in AI and machine learning.Applicants from all backgrounds are welcome! Ideally,... |
https://huggingface.co/blog/diffusion-models-event | Diffusion Models Live Event | Lewis Tunstall, Jonathan Whitaker | November 25, 2022 | We are excited to share that the Diffusion Models Class with Hugging Face and Jonathan Whitaker will be released on November 28th 🥳! In this free course, you will learn all about the theory and application of diffusion models -- one of the most exciting developments in deep learning this year. If you've never heard of... |
https://huggingface.co/blog/document-ai | Accelerating Document AI | Rajiv Shah, Niels Rogge, Florent Gbelidji, Nicholas Broad | November 21, 2022 | Enterprises are full of documents containing knowledge that isn't accessible by digital workflows. These documents can vary from letters, invoices, forms, reports, to receipts. With the improvements in text, vision, and multimodal AI, it's now possible to unlock that information. This post shows you how your teams can ... |
https://huggingface.co/blog/inference-update | An Overview of Inference Solutions on Hugging Face | Julien Simon | November 21, 2022 | Every day, developers and organizations are adopting models hosted on Hugging Face to turn ideas into proof-of-concept demos, and demos into production-grade applications. For instance, Transformer models have become a popular architecture for a wide range of machine learning (ML) applications, including natural langua... |
https://huggingface.co/blog/ml-director-insights-4 | Director of Machine Learning Insights [Part 4] | No authors found | November 23, 2022 | If you're interested in building ML solutions faster visit: hf.co/support today!👋 Welcome back to our Director of ML Insights Series! If you missed earlier Editions you can find them here:Director of Machine Learning Insights [Part 1]Director of Machine Learning Insights [Part 2 : SaaS Edition]Director of Machine Lear... |
https://huggingface.co/blog/arxiv | Hugging Face Machine Learning Demos on arXiv | Abubakar Abid, Omar Sanseviero, Pedro Cuenca | November 17, 2022 | Hugging Face Machine Learning Demos on arXivHugging Face Models Datasets Spaces Posts Docs Solutions Pricing Log In Sign Up Back to Articles Hugging Face Machine Learning Demos on arXiv |
https://huggingface.co/blog/sentiment-analysis-fhe | Sentiment Analysis on Encrypted Data with Homomorphic Encryption | Jordan Frery | November 17, 2022 | It is well-known that a sentiment analysis model determines whether a text is positive, negative, or neutral. However, this process typically requires access to unencrypted text, which can pose privacy concerns.Homomorphic encryption is a type of encryption that allows for computation on encrypted data without needing ... |
https://huggingface.co/blog/introducing-csearch | Generating Human-level Text with Contrastive Search in Transformers 🤗 | Tian Lan | November 8, 2022 | Natural language generation (i.e. text generation) is one of the core tasks in natural language processing (NLP). In this blog, we introduce the current state-of-the-art decoding method, Contrastive Search, for neural text generation. Contrastive search is originally proposed in "A Contrastive Framework for Neural Text... |
https://huggingface.co/blog/pricing-update | Introducing our new pricing | Simon Brandeis, Pierric Cistac | November 8, 2022 | Introducing our new pricingHugging FaceModelsDatasetsSpacesPostsDocsSolutionsPricingLog InSign UpBack to ArticlesIntroducing our new pricing |
https://huggingface.co/blog/dreambooth | Training Stable Diffusion with Dreambooth using 🧨 Diffusers | Suraj Patil, Pedro Cuenca, Valentine Kozin | November 7, 2022 | Dreambooth is a technique to teach new concepts to Stable Diffusion using a specialized form of fine-tuning. Some people have been using it with a few of their photos to place themselves in fantastic situations, while others are using it to incorporate new styles. 🧨 Diffusers provides a Dreambooth training script. It ... |
https://huggingface.co/blog/fine-tune-whisper | Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers | Sanchit Gandhi | November 3, 2022 | In this blog, we present a step-by-step guide on fine-tuning Whisper for any multilingual ASR dataset using Hugging Face 🤗 Transformers. This blog provides in-depth explanations of the Whisper model, the Common Voice dataset and the theory behind fine-tuning, with accompanying code cells to execute the data preparatio... |
https://huggingface.co/blog/openvino | Accelerate your models with 🤗 Optimum Intel and OpenVINO | Ella Charlaix, Julien Simon | November 2, 2022 | Last July, we announced that Intel and Hugging Face would collaborate on building state-of-the-art yet simple hardware acceleration tools for Transformer models. Today, we are very happy to announce that we added Intel OpenVINO to Optimum Intel. You can now easily perform inference with OpenVINO Runtime on a variety o... |
https://huggingface.co/blog/evaluating-llm-bias | Evaluating Language Model Bias with 🤗 Evaluate | Sasha Luccioni, Margaret Mitchell, helen, Leandro von Werra, Douwe Kiela | October 24, 2022 | While the size and capabilities of large language models have drastically increased over the past couple of years, so too has the concern around biases imprinted into these models and their training data. In fact, many popular language models have been found to be biased against specific religions and genders, which ca... |
https://huggingface.co/blog/pytorch-ddp-accelerate-transformers | From PyTorch DDP to Accelerate to Trainer, mastery of distributed training with ease | Zachary Mueller | October 21, 2022 | General Overview This tutorial assumes you have a basic understanding of PyTorch and how to train a simple model. It will showcase training on multiple GPUs through a process called Distributed Data Parallelism (DDP) through three different levels of increasing abstraction:Native PyTorch DDP through the pytorch.distrib... |
https://huggingface.co/blog/mteb | MTEB: Massive Text Embedding Benchmark | Niklas Muennighoff | October 19, 2022 | MTEB is a massive benchmark for measuring the performance of text embedding models on diverse embedding tasks.The 🥇 leaderboard provides a holistic view of the best text embedding models out there on a variety of tasks. The 📝 paper gives background on the tasks and datasets in MTEB and analyzes leaderboard results!Th... |
https://huggingface.co/blog/inference-endpoints | Getting Started with Hugging Face Inference Endpoints | Julien Simon | October 14, 2022 | Training machine learning models has become quite simple, especially with the rise of pre-trained models and transfer learning. OK, sometimes it's not that simple, but at least, training models will never break critical applications, and make customers unhappy about your quality of service. Deploying models, however...... |
https://huggingface.co/blog/stable_diffusion_jax | 🧨 Stable Diffusion in JAX / Flax ! | Pedro Cuenca, Patrick von Platen | October 13, 2022 | 🤗 Hugging Face Diffusers supports Flax since version 0.5.1! This allows for super fast inference on Google TPUs, such as those available in Colab, Kaggle or Google Cloud Platform.This post shows how to run inference using JAX / Flax. If you want more details about how Stable Diffusion works or want to run it in GPU, p... |
https://huggingface.co/blog/bloom-inference-optimization | Optimization story: Bloom inference | Nicolas Patry | October 12, 2022 | This article gives you the behind-the-scenes of how we made an efficient inference server that powers bloom.inference server that powers https://huggingface.co/bigscience/bloom.We achieved a 5x latency reduction over several weeks (and 50x more throughput). We wanted to share all the struggles and epic wins we went thr... |
https://huggingface.co/blog/introducing-doi | Introducing DOI: the Digital Object Identifier to Datasets and Models | Sasha Luccioni, Sylvestre Bcht, Christopher Akiki, Alix Leroy | October 7, 2022 | Our mission at Hugging Face is to democratize good machine learning. That includes best practices that make ML models and datasets more reproducible, better documented, and easier to use and share.To solve this challenge, we're excited to announce that you can now generate a DOI for your model or dataset directly from ... |
https://huggingface.co/blog/japanese-stable-diffusion | Japanese Stable Diffusion | Kei Sawada | October 5, 2022 | Stable Diffusion, developed by CompVis, Stability AI, and LAION, has generated a great deal of interest due to its ability to generate highly accurate images by simply entering text prompts. Stable Diffusion mainly uses the English subset LAION2B-en of the LAION-5B dataset for its training data and, as a result, requir... |
https://huggingface.co/blog/zero-shot-eval-on-the-hub | Very Large Language Models and How to Evaluate Them | helen, Tristan Thrush, Abhishek Thakur, Lewis Tunstall, Douwe Kiela | October 3, 2022 | Large language models can now be evaluated on zero-shot classification tasks with Evaluation on the Hub! Zero-shot evaluation is a popular way for researchers to measure the performance of large language models, as they have been shown to learn capabilities during training without explicitly being shown labeled example... |
https://huggingface.co/blog/autotrain-image-classification | Image Classification with AutoTrain | Nima Boscarino | September 28, 2022 | So you’ve heard all about the cool things that are happening in the machine learning world, and you want to join in. There’s just one problem – you don’t know how to code! 😱 Or maybe you’re a seasoned software engineer who wants to add some ML to your side-project, but you don’t have the time to pick up a whole new te... |
https://huggingface.co/blog/accelerate-large-models | How 🤗 Accelerate runs very large models thanks to PyTorch | Sylvain Gugger | September 27, 2022 | Load and run large modelsMeta AI and BigScience recently open-sourced very large language models which won't fit into memory (RAM or GPU) of most consumer hardware. At Hugging Face, part of our mission is to make even those large models accessible, so we developed tools to allow you to run those models even if you don'... |
https://huggingface.co/blog/setfit | SetFit: Efficient Few-Shot Learning Without Prompts | Unso Eun Seo Jo, Lewis Tunstall, Luke Bates, Oren Pereg, Moshe Wasserblat | September 26, 2022 | Few-shot learning with pretrained language models has emerged as a promising solution to every data scientist's nightmare: dealing with data that has few to no labels 😱.Together with our research partners at Intel Labs and the UKP Lab, Hugging Face is excited to introduce SetFit: an efficient framework for few-shot fi... |
https://huggingface.co/blog/ethics-soc-1 | Ethics and Society Newsletter #1 | Margaret Mitchell | September 22, 2022 | Ethics and Society Newsletter #1Hugging FaceModelsDatasetsSpacesPostsDocsSolutionsPricingLog InSign UpBack to ArticlesEthics and Society Newsletter #1 |
https://huggingface.co/blog/bloom-inference-pytorch-scripts | Incredibly Fast BLOOM Inference with DeepSpeed and Accelerate | Stas Bekman, Sylvain Gugger | September 16, 2022 | This article shows how to get an incredibly fast per token throughput when generating with the 176B parameter BLOOM model.As the model needs 352GB in bf16 (bfloat16) weights (176*2), the most efficient set-up is 8x80GB A100 GPUs. Also 2x8x40GB A100s or 2x8x48GB A6000 can be used. The main reason for using these GPUs is... |
https://huggingface.co/blog/megatron-training | How to train a Language Model with Megatron-LM | Loubna Ben Allal | September 7, 2022 | Training large language models in Pytorch requires more than a simple training loop. It is usually distributed across multiple devices, with many optimization techniques for a stable and efficient training. Hugging Face 🤗 Accelerate library was created to support distributed training across GPUs and TPUs with very eas... |
https://huggingface.co/blog/diffusers-2nd-month | What's new in Diffusers? 🎨 | Omar Sanseviero | September 12, 2022 | A month and a half ago we released diffusers, a library that provides a modular toolbox for diffusion models across modalities. A couple of weeks later, we released support for Stable Diffusion, a high quality text-to-image model, with a free demo for anyone to try out. Apart from burning lots of GPUs, in the last thre... |
https://huggingface.co/blog/train-decision-transformers | Train your first Decision Transformer | Edward Beeching, Thomas Simonini | September 8, 2022 | In a previous post, we announced the launch of Decision Transformers in the transformers library. This new technique of using a Transformer as a Decision-making model is getting increasingly popular.So today, you’ll learn to train your first Offline Decision Transformer model from scratch to make a half-cheetah run. We... |
https://huggingface.co/blog/open_rail | OpenRAIL: Towards open and responsible AI licensing frameworks | Carlos Muñoz Ferrandis | August 31, 2022 | Open & Responsible AI licenses ("OpenRAIL") are AI-specific licenses enabling open access, use and distribution of AI artifacts while requiring a responsible use of the latter. OpenRAIL licenses could be for open and responsible ML what current open software licenses are to code and Creative Commons to general content:... |
https://huggingface.co/blog/spaces_3dmoljs | Visualize proteins on Hugging Face Spaces | Simon Duerr | August 24, 2022 | In this post we will look at how we can visualize proteins on Hugging Face Spaces.Motivation 🤗Proteins have a huge impact on our life - from medicines to washing powder. Machine learning on proteins is a rapidly growing field to help us design new and interesting proteins. Proteins are complex 3D objects generally com... |
https://huggingface.co/blog/stable_diffusion | Stable Diffusion with 🧨 Diffusers | Suraj Patil, Pedro Cuenca, Nathan Lambert, Patrick von Platen | August 22, 2022 | Stable Diffusion 🎨 ...using 🧨 DiffusersStable 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 512x512 images from a subset of the LAION-5B database.LAION-5B is the largest, freely accessible multi-modal dataset that cu... |
https://huggingface.co/blog/pretraining-bert | Pre-Training BERT with Hugging Face Transformers and Habana Gaudi | Philipp Schmid | August 22, 2022 | 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 model... |
https://huggingface.co/blog/deploy-vertex-ai | Deploying 🤗 ViT on Vertex AI | Sayak Paul, chansung park | August 19, 2022 | In the previous posts, we showed how to deploy a Vision Transformers(ViT) modelfrom 🤗 Transformers locally andon a Kubernetes cluster. This post willshow you how to deploy the same model on the Vertex AI platform.You’ll achieve the same scalability level as Kubernetes-based deployment but withsignificantly less code. ... |
https://huggingface.co/blog/vision-transformers | Deep Dive: Vision Transformers On Hugging Face Optimum Graphcore | Julien Simon | August 18, 2022 | Deep Dive: Vision Transformers On Hugging Face Optimum GraphcoreHugging Face Models Datasets Spaces Posts Docs Solutions Pricing Log In Sign Up Back to Articles Deep Dive: Vision Transformers On Hugging Face Optimum Graphcore |
https://huggingface.co/blog/hf-bitsandbytes-integration | A Gentle Introduction to 8-bit Matrix Multiplication for transformers at scale using Hugging Face Transformers, Accelerate and bitsandbytes | Younes Belkada, Tim Dettmers | August 17, 2022 | IntroductionLanguage models are becoming larger all the time. At the time of this writing, PaLM has 540B parameters, OPT, GPT-3, and BLOOM have around 176B parameters, and we are trending towards even larger models. Below is a diagram showing the size of some recent language models.Therefore, these models are hard to r... |
https://huggingface.co/blog/skops | Introducing Skops | Merve Noyan, Adrin Jalali, Benjamin Bossan | August 12, 2022 | Introducing SkopsAt Hugging Face, we are working on tackling various problems in open-source machine learning, including, hosting models securely and openly, enabling reproducibility, explainability and collaboration. We are thrilled to introduce you to our new library: Skops! With Skops, you can host your scikit-learn... |
https://huggingface.co/blog/tensorflow-philosophy | Hugging Face's TensorFlow Philosophy | Matthew Carrigan | August 12, 2022 | 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, and its data loading library tf.data.There is a tendency ... |
https://huggingface.co/blog/deploy-tfserving-kubernetes | Deploying 🤗 ViT on Kubernetes with TF Serving | chansung park, Sayak Paul | August 11, 2022 | In the previous post, we showed howto deploy a Vision Transformer (ViT)model from 🤗 Transformers locally with TensorFlow Serving. We coveredtopics like embedding preprocessing and postprocessing operations withinthe Vision Transformer model, handling gRPC requests, and more!While local deployments are an excellent hea... |
https://huggingface.co/blog/how-to-train-sentence-transformers | Train and Fine-Tune Sentence Transformers Models | Omar Espejel | August 10, 2022 | 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 key is twofold: Understand how to input data into the model and prepare your dataset accordingly.Know the different loss functions and how they relate t... |
https://huggingface.co/blog/deep-rl-ppo | Proximal Policy Optimization (PPO) | Thomas Simonini | August 5, 2022 | Unit 8, of the Deep Reinforcement Learning Class with Hugging Face 🤗⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introductionThis article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here.⚠️ A ne... |
https://huggingface.co/blog/introducing-private-hub | Introducing the Private Hub: A New Way to Build With Machine Learning | Federico Pascual | August 3, 2022 | 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 off... |
https://huggingface.co/blog/nystromformer | Nyströmformer: Approximating self-attention in linear time and memory via the Nyström method | Antoine SIMOULIN | August 2, 2022 | IntroductionTransformers have exhibited remarkable performance on various Natural Language Processing and Computer Vision tasks. Their success can be attributed to the self-attention mechanism, which captures the pairwise interactions between all the tokens in an input. However, the standard self-attention mechanism ha... |
https://huggingface.co/blog/us-national-ai-research-resource | AI Policy @🤗: Comments on U.S. National AI Research Resource Interim Report | Irene Solaiman | August 1, 2022 | Comments on U.S. National AI Research Resource Interim ReportHugging FaceModelsDatasetsSpacesPostsDocsSolutionsPricingLog InSign UpBack to ArticlesAI Policy @🤗: Comments on U.S. National AI Research Resource Interim Report |
https://huggingface.co/blog/datasets-docs-update | Introducing new audio and vision documentation in 🤗 Datasets | Steven Liu | July 28, 2022 | Open and reproducible datasets are essential for advancing good machine learning. At the same time, datasets have grown tremendously in size as rocket fuel for large language models. In 2020, Hugging Face launched 🤗 Datasets, a library dedicated to:Providing access to standardized datasets with a single line of code.T... |
https://huggingface.co/blog/tf-xla-generate | Faster Text Generation with TensorFlow and XLA | Joao Gante | July 27, 2022 | TL;DR: Text Generation on 🤗 transformers using TensorFlow can now be compiled with XLA. It is up to 100xfaster than before, and even faster than PyTorch-- check the colab below!Text GenerationAs the quality of large language models increased, so did our expectations of what those models could do. Especiallysince the r... |
https://huggingface.co/blog/tf-serving-vision | Deploying TensorFlow Vision Models in Hugging Face with TF Serving | Sayak Paul | July 25, 2022 | In the past few months, the Hugging Face team and external contributorsadded a variety of vision models in TensorFlow to Transformers. Thislist is growing comprehensively and already includes state-of-the-artpre-trained models like Vision Transformer,Masked Autoencoders,RegNet,ConvNeXt,and many others!When it comes to ... |
https://huggingface.co/blog/deep-rl-a2c | Advantage Actor Critic (A2C) | Thomas Simonini | July 22, 2022 | Unit 7, of the Deep Reinforcement Learning Class with Hugging Face 🤗⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introductionThis article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here.⚠️ A ne... |
https://huggingface.co/blog/mnist-adversarial | How to train your model dynamically using adversarial data | Chris Emezue | July 16, 2022 | Dynamic adversarial data collection (DADC)Static benchmarks, while being a widely-used way to evaluate your model's performance, are fraught with many issues: they saturate, have biases or loopholes, and often lead researchers to chase increment in metrics instead of building trustworthy models that can be used by huma... |
https://huggingface.co/blog/bloom-megatron-deepspeed | The Technology Behind BLOOM Training | Stas Bekman | July 14, 2022 | In recent years, training ever larger language models has become the norm. While the issues of those models' not being released for further study is frequently discussed, the hidden knowledge about how to train such models rarely gets any attention. This article aims to change this by shedding some light on the technol... |
https://huggingface.co/blog/playlist-generator | Building a Playlist Generator with Sentence Transformers | Nima Boscarino | July 13, 2022 | A short while ago I published a playlist generator that I’d built using Sentence Transformers and Gradio, and I followed that up with a reflection on how I try to use my projects as effective learning experiences. But how did I actually build the playlist generator? In this post we’ll break down that project and look a... |
https://huggingface.co/blog/bloom | 🌸 Introducing The World's Largest Open Multilingual Language Model: BLOOM 🌸 | BigScience Workshop | July 12, 2022 | Introducing The World's Largest Open Multilingual Language Model: BLOOMHugging FaceModelsDatasetsSpacesPostsDocsSolutionsPricingLog InSign UpBack to Articles🌸 Introducing The World's Largest Open Multilingual Language Model: BLOOM 🌸 |
https://huggingface.co/blog/sentiment-analysis-twitter | Getting Started with Sentiment Analysis on Twitter | Federico Pascual | July 7, 2022 | Sentiment analysis is the automatic process of classifying text data according to their polarity, such as positive, negative and neutral. Companies leverage sentiment analysis of tweets to get a sense of how customers are talking about their products and services, get insights to drive business decisions, and identify ... |
https://huggingface.co/blog/deep-rl-pg | Policy Gradient with PyTorch | Thomas Simonini | June 30, 2022 | Unit 5, of the Deep Reinforcement Learning Class with Hugging Face 🤗⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introductionThis article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here.⚠️ A ne... |
https://huggingface.co/blog/your-first-ml-project | Liftoff! How to get started with your first ML project 🚀 | Nima Boscarino | June 29, 2022 | People who are new to the Machine Learning world often run into two recurring stumbling blocks. The first is choosing the right library to learn, which can be daunting when there are so many to pick from. Even once you’ve settled on a library and gone through some tutorials, the next issue is coming up with your first ... |
https://huggingface.co/blog/accelerate-deepspeed | Accelerate Large Model Training using DeepSpeed | Sourab Mangrulkar, Sylvain Gugger | June 28, 2022 | In this post we will look at how we can leverage the Accelerate library for training large models which enables users to leverage the ZeRO features of DeeSpeed. Motivation 🤗 Tired of Out of Memory (OOM) errors while trying to train large models? We've got you covered. Large models are very performant [1] but difficul... |
https://huggingface.co/blog/eval-on-the-hub | Announcing Evaluation on the Hub | Lewis Tunstall, Abhishek Thakur, Tristan Thrush, Sasha Luccioni, Leandro von Werra, Nazneen Rajani, Aleksandra Piktus, Omar Sanseviero, Douwe Kiela | June 28, 2022 | This project has been archived. If you want to evaluate LLMs on the Hub, check out this collection of leaderboards.TL;DR: Today we introduce Evaluation on the Hub, a new tool powered by AutoTrain that lets you evaluate any model on any dataset on the Hub without writing a single line of code!Evaluate all the models 🔥�... |
https://huggingface.co/blog/getting-started-with-embeddings | Getting Started With Embeddings | Omar Espejel | June 23, 2022 | Check out this tutorial with the Notebook Companion:Understanding embeddingsAn embedding is a numerical representation of a piece of information, for example, text, documents, images, audio, etc. The representation captures the semantic meaning of what is being embedded, making it robust for many industry applications.... |
https://huggingface.co/blog/convert-transformers-to-onnx | Convert Transformers to ONNX with Hugging Face Optimum | Philipp Schmid | June 22, 2022 | Hundreds of Transformers experiments and models are uploaded to the Hugging Face Hub every single day. Machine learning engineers and students conducting those experiments use a variety of frameworks like PyTorch, TensorFlow/Keras, or others. These models are already used by thousands of companies and form the foundati... |
https://huggingface.co/blog/intel | Intel and Hugging Face Partner to Democratize Machine Learning Hardware Acceleration | Julien Simon | June 15, 2022 | The mission of Hugging Face is to democratize good machine learning and maximize its positive impact across industries and society. Not only do we strive to advance Transformer models, but we also work hard on simplifying their adoption.Today, we're excited to announce that Intel has officially joined our Hardware Part... |
https://huggingface.co/blog/ml-director-insights-3 | Director of Machine Learning Insights [Part 3: Finance Edition] | Britney Muller | June 14, 2022 | If you're interested in building ML solutions faster visit hf.co/support today!👋 Welcome back to our Director of ML Insights Series, Finance Edition! If you missed earlier Editions you can find them here:Director of Machine Learning Insights [Part 1]Director of Machine Learning Insights [Part 2 : SaaS Edition]Machine ... |
https://huggingface.co/blog/annotated-diffusion | The Annotated Diffusion Model | Niels Rogge, Kashif Rasul | June 7, 2022 | In this blog post, we'll take a deeper look into Denoising Diffusion Probabilistic Models (also known as DDPMs, diffusion models, score-based generative models or simply autoencoders) as researchers have been able to achieve remarkable results with them for (un)conditional image/audio/video generation. Popular examples... |
https://huggingface.co/blog/deep-rl-dqn | Deep Q-Learning with Space Invaders | Thomas Simonini | June 7, 2022 | Unit 3, of the Deep Reinforcement Learning Class with Hugging Face 🤗⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introductionThis article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here.⚠️ A ne... |
https://huggingface.co/blog/graphcore-update | Graphcore and Hugging Face Launch New Lineup of IPU-Ready Transformers | Sally Doherty | May 26, 2022 | Graphcore and Hugging Face have significantly expanded the range of Machine Learning modalities and tasks available in Hugging Face Optimum, an open-source library for Transformers performance optimization. Developers now have convenient access to a wide range of off-the-shelf Hugging Face Transformer models, optimised... |
https://huggingface.co/blog/community-update | Introducing Pull Requests and Discussions 🥳 | No authors found | May 25, 2022 | We are thrilled to announce the release of our latest collaborative features: pull requests and discussions on the Hugging Face Hub!Pull requests and discussions are available today under the community tab for all repository types: models, datasets, and Spaces. Any member of the community can create and participate in ... |
https://huggingface.co/blog/tapex | Efficient Table Pre-training without Real Data: An Introduction to TAPEX | Qian Liu | May 23, 2022 | In recent years, language model pre-training has achieved great success via leveraging large-scale textual data. By employing pre-training tasks such as masked language modeling, these models have demonstrated surprising performance on several downstream tasks. However, the dramatic gap between the pre-training task (e... |
https://huggingface.co/blog/deep-rl-q-part2 | An Introduction to Q-Learning Part 2/2 | Thomas Simonini | May 20, 2022 | Unit 2, part 2 of the Deep Reinforcement Learning Class with Hugging Face 🤗⚠️ A new updated version of this article is available here 👉 https://huggingface.co/deep-rl-course/unit1/introductionThis article is part of the Deep Reinforcement Learning Class. A free course from beginner to expert. Check the syllabus here.... |
https://huggingface.co/blog/sempre-health-eap-case-study | How Sempre Health is leveraging the Expert Acceleration Program to accelerate their ML roadmap | Hugging Face | May 19, 2022 | 👋 Hello, friends! We recently sat down with Swaraj Banerjee and Larry Zhang from Sempre Health, a startup that brings behavior-based, dynamic pricing to Healthcare. They are doing some exciting work with machine learning and are leveraging our Expert Acceleration Program to accelerate their ML roadmap.An example of ou... |
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