This is an example on how to deploy the open-source LLMs, like BLOOM to Amazon SageMaker for inference using the new Hugging Face LLM Inference Container. We will deploy the 12B Pythia Open Assistant Model, an open-source Chat LLM trained with the Open Assistant dataset. The example covers: Setup development environment Retrieve the new Hugging Face    

Introduction This tutorial guides you through the process of implementing state-of-the-art Speech Recognition in your Unity game using the Hugging Face Unity API. This feature can be used for giving commands, speaking    

Falcon is a new family of state-of-the-art language models created by the Technology Innovation Institute in Abu Dhabi, and released under the Apache 2.0 license. Notably, Falcon-40B is the first “truly open” model with capabilities rivaling many current closed-source models. This is fantastic news for practitioners, enthusiasts, and industry, as it opens the door for many exciting use cases. Note: Few months after this release, the Falcon team released a larger model of 180 billion parameters. September 2023 Update: Falcon […]

fastText is a library for efficient learning of text representation and classification. Open-sourced by Meta AI in 2016, fastText integrates key ideas that have been influential in natural language processing and machine learning over the    

The Hugging Face Hub is dedicated to providing open access to datasets for everyone and giving users the tools to explore and understand them. You can find many of the datasets used to train popular large language models (LLMs) like Falcon, Dolly, MPT, and StarCoder. There are tools for addressing fairness and bias in datasets like Disaggregators, and tools for previewing examples inside a dataset like the Dataset Viewer. A preview of the OpenAssistant dataset with the Dataset Viewer. We […]

Since the advent of ChatGPT, we have seen unprecedented growth in the development of Large Language    

Whether language models, large language models, or foundation models, transformers require significant computation for pre-training, fine-tuning, and inference. To help developers and organizations get the most performance bang for their infrastructure bucks, Hugging Face has long been working with hardware companies to leverage acceleration features present on their respective chips. Today, we’re happy to announce that AMD has officially    

The Elixir community has been making great strides towards Machine Learning and Hugging Face is playing an important role on making it possible. To showcase what you can already achieve with Elixir and Machine Learning today, we use Livebook to build a Whisper-based chat app and then deploy it to Hugging Face Spaces. All under 15 minutes, check