LLMs are known to be large, and running or training them in consumer hardware is a huge challenge for users and accessibility. Our LLM.int8 blogpost showed how the techniques in the LLM.int8 paper were integrated in transformers using the bitsandbytes library. As we strive to make models even more accessible to anyone, we decided to collaborate with bitsandbytes again to allow users to run models in 4-bit precision. This includes a large majority of HF models, in any modality (text, […]

Latent Diffusion models are game changers when it comes to solving text-to-image generation problems. Stable Diffusion is one of the most famous examples that got wide adoption in the community and industry. The idea behind the Stable Diffusion model is simple and compelling: you generate an image from a noise vector in multiple small steps refining the noise to a latent image representation. This approach works very well, but it can take a long time to generate an image if […]

-1 language – models – model – data – based 20 -1_language_models_model_data 0 dialogue – dialog – response – responses – intent 14247 0_dialogue_dialog_response_responses 1 speech – asr – speech recognition – recognition – end 1833 1_speech_asr_speech recognition_recognition 2 tuning – tasks – prompt – models – language 1369 2_tuning_tasks_prompt_models 3 summarization – summaries – summary – abstractive – document 1109 3_summarization_summaries_summary_abstractive 4 question – answer – qa – answering – question answering 893 4_question_answer_qa_answering 5 sentiment – sentiment analysis […]

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