This is an official tutorial article from Hugging Face that guides developers on how to fine-tune a Vision Transformer (ViT) model for image classification…
This is a practical tutorial guide written by Hugging Face, designed to help developers and data scientists quickly get started with sentiment analysis using…
Hugging Face's official blog has announced a major upgrade to its platform's core feature — the search functionality of Hugging Face Hub. As the open-source AI…
Hugging Face has officially announced a deep integration with the popular PyTorch reinforcement learning (RL) library Stable-baselines3 (SB3). This…
With the rise of open-source large language models, deploying these models in cloud environments in a secure, stable, and scalable manner has become a critical…
On December 21, 2021, the open-source machine learning world received major news: Gradio, the open-source library purpose-built for rapidly creating…
This classic Hugging Face blog post documents the birth of the "CodeParrot" project — an experiment in training a code generation model entirely from scratch…
This blog post introduces the fruits of a collaboration between Hugging Face and hardware chip design company Graphcore, showcasing how to use Hugging Face's…
This announcement comes from the official Hugging Face blog, published in October 2021, celebrating the launch of the Hugging Face Course along with an…
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…
This classic Hugging Face blog post (co-authored by Sentence-Transformers creator Nils Reimers and others) provides a detailed account of how to train…
This blog post from the Hugging Face community provides a detailed walkthrough of how to fine-tune OpenAI's CLIP (Contrastive Language-Image Pre-training)…
The summer of 2021 was a vibrant and breakthrough season for Hugging Face. In this retrospective, Hugging Face summarizes the rich achievements produced over…
Hugging Face has officially launched a new open-source toolkit called "Optimum" — an optimization and hardware acceleration library designed specifically for…
Hugging Face officially announced a deep integration with spaCy, the popular industrial-grade natural language processing (NLP) framework, formally bringing…
Hugging Face and Amazon Web Services (AWS) have entered into a deep collaboration aimed at simplifying the deployment process of machine learning models from…
In the field of natural language processing (NLP), the emergence of GPT-3 demonstrated the tremendous power of "Few-shot Learning" — where a model only needs…
In May 2021, Gradio officially released version 2.0 and announced a deep integration with the Hugging Face platform. This collaboration fundamentally changed…
In many real-world enterprise production environments, although GPUs offer extremely high throughput for deep learning inference, CPUs remain indispensable due…
This technical guide, published by Hugging Face in 2021, details how to use Amazon SageMaker's managed infrastructure and distributed training capabilities to…
Hugging Face has officially announced a deep partnership with Amazon Web Services (AWS), aimed at natively integrating the Hugging Face Transformers platform…
This article is a hands-on experience report from the author on deploying a Hugging Face Transformers pipeline to a serverless environment on Google Cloud…
This is a landmark technical tutorial published by the Hugging Face team in 2021, detailing how to fine-tune Meta AI's Wav2Vec2 model using the Hugging Face…
In the field of natural language processing (NLP), the core of standard Transformer models (such as BERT and GPT-2) is the self-attention mechanism. However…
Retrieval-Augmented Generation (RAG) is a powerful architecture that combines a "retriever" with a "generator." It enables language models to dynamically…
Hugging Face has announced a deep collaboration with Google Cloud, officially adding support for PyTorch/XLA within its ecosystem. The goal is to address the…
As the parameter scale of Transformer models (such as GPT, T5, etc.) grows exponentially, deep learning faces a severe "Memory Wall" challenge. With limited…
In this technical blog post, the Hugging Face team reveals in detail how they achieved up to 100x speedup in inference for Transformer models for customers of…
In the field of natural language processing (NLP), machine translation has always been a core challenge. Facebook AI Research (FAIR) achieved outstanding…
This classic blog post written by Hugging Face researcher Patrick von Platen takes a deep dive into the Transformer-based Encoder-Decoder model architecture…