The important moves in artificial intelligence.

A research agenda for assessing the economic impacts of code generation models

BERT 101 - State Of The Art NLP Model Explained

Fine-Tune ViT for Image Classification with 🤗 Transformers

Solving (some) formal math olympiad problems

We built a neural theorem prover for Lean that learned to solve a variety of challenging high-school olympiad problems, including problems from the AMC12 and AIME competitions, as well as two problems adapted from the IMO.

Getting Started with Sentiment Analysis using Python

Making automatic speech recognition work on large files with Wav2Vec2 in 🤗 Transformers

Aligning language models to follow instructions

We’ve trained language models that are much better at following user intentions than GPT-3 while also making them more truthful and less toxic, using techniques developed through our alignment research. These InstructGPT models, which are trained with humans in the loop, are now deployed as the default language models on our API.

Introducing text and code embeddings

We are introducing embeddings, a new endpoint in the OpenAI API that makes it easy to perform natural language and code tasks like semantic search, clustering, topic modeling, and classification.

Supercharged Searching on the 🤗 Hub

Text and code embeddings by contrastive pre-training

Welcome Stable-baselines3 to the Hugging Face Hub 🤗

Case Study: Millisecond Latency using Hugging Face Infinity and modern CPUs