In the development of large language models (LLMs), RLHF (Reinforcement Learning from Human Feedback) is the critical step for aligning models with human…
In the machine learning field, deploying research-stage models to production environments — such as packaging them into Docker containers or deploying them to…
This article explains how to accelerate the deployment and inference of Hugging Face Transformers models using AWS Inferentia2 (Inf2 instances) — AWS's…
At the height of the generative AI explosion in early 2023, developers building LLM (Large Language Model) applications faced two major pain points: OpenAI API…
With the explosion of generative AI, developers deploying AI applications (such as chatbots and image generators) face two major challenges: Serverless…
Amid the generative AI wave sparked by ChatGPT, Hugging Face published this in-depth article exploring how to transform "base language models" — which can only…
This practical tutorial from Hugging Face kicks off a series documenting the challenge of building a game with AI assistance in 5 days. In the first…
In December 2022, Elixir language creator José Valim and Hugging Face jointly announced a transformative project for the Elixir community: Bumblebee. The…
The release of ChatGPT in late 2022 triggered an explosion in generative AI, and the most critical technology behind it is Reinforcement Learning from Human…
In the field of natural language generation (NLG), enabling language models to produce coherent and natural long-form text has long been a major challenge…
As language model scales continue to expand, the memory (VRAM) of a single GPU has long been unable to accommodate models with tens or hundreds of billions of…
This classic Hugging Face blog post documents the birth of the "CodeParrot" project — an experiment in training a code generation model entirely from scratch…
In late 2021, the AI field witnessed an unprecedented explosive growth in large language models (LLMs). From OpenAI's GPT-3 at 175 billion parameters to the…
In the field of natural language processing (NLP), sequence-to-sequence (Seq2Seq) models — such as those used for translation or summarization — typically…