Researchers and developers can now easily master distributed training techniques using popular frameworks like PyTorch DDP, Accelerate, and Trainer. T...
A study on scaling laws for reward model overoptimization has been published by OpenAI. The researchers identified that as the number of parameters in...
MTEB is a benchmark for evaluating the performance of text embedding models. It consists of a large dataset with over 1 million examples and supports ...
Hugging Face's Inference Endpoints allow developers to easily deploy and manage AI models in the cloud. With this tool, users can create a single endp...
Hugging Face has released a version of the Stable Diffusion model optimized for use with the JAX and Flax frameworks. This allows developers to run th...
Researchers have published an optimization story for the Bloom model, a large language model developed by Meta AI. The team used various techniques to...
Hugging Face has introduced a new system called DOI, or Digital Object Identifier, which assigns unique identifiers to datasets and models. This allow...
Researchers have adapted the popular AI model Stable Diffusion to generate images in Japanese. The model was trained on a dataset of Japanese text and...
Large language models are being used for a wide range of applications, from text generation to question answering. However, evaluating their performan...
OpenAI's DALL·E model is now available without a waitlist, allowing new users to create content immediately. This change comes after lessons were lear...
Hugging Face has released AutoTrain, a tool for image classification tasks that automates the process of model selection and hyperparameter tuning. Th...
Hugging Face's 🤗 Accelerate library has improved performance for running very large AI models. This is achieved through the use of PyTorch, a popular ...