Hugging Face stores over 30 PB of models, datasets, and spaces in Git LFS repositories. Because Git stores and versions...
AI Content Creation
In the world of web development, turning designs into functional websites usually involves a lot of coding and careful testing....
Embedding models are useful for many applications such as retrieval, reranking, clustering, and classification. The research community has witnessed significant...
Self-speculative decoding, proposed in LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding is a novel approach to text generation. It...
LLMs are now increasingly capable in English, but it's quite hard to know how well they perform in other national...
Today, we are thrilled to announce the launch of Train on DGX Cloud, a new service on the Hugging Face...
Quantization is a technique to reduce the computational and memory costs of evaluating Deep Learning Models by representing their weights...
Because of their impressive abilities, large language models (LLMs) require significant computing power, which is seldom available on personal computers....
In this blog post, we outline the challenges and solutions involved in generating a synthetic dataset with billions of tokens...
The integration of GaLore into the training of large language models (LLMs) marks a significant advancement in the field of...
