Hugging Face stores over 30 PB of models, datasets, and spaces in Git LFS repositories, but the current file-level versioning system is inefficient, requiring re-uploading full assets for small changes.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 80 | 2024-11-20 05:00:32 PM |
A novel approach to text generation, self-speculative decoding, combines strengths of speculative decoding and early exiting from a large language model to achieve faster text generation, memory savings, and reduced computational latency.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 86 | 2024-11-20 12:40:35 PM |
The Open Japanese LLM Leaderboard, a project by LLM-jp and Hugging Face, evaluates over 20 Japanese datasets for various NLP tasks. This aims to better understand Japanese LLMs and their capabilities.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 80 | 2024-11-20 09:00:39 AM |
Judge Arena is a platform that allows users to compare and rank language models as judges based on their performance in evaluating natural language outputs.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 86 | 2024-11-19 01:01:12 PM |
Hugging Face Hub, a platform trusted by various institutions, allows researchers and machine learning professionals to easily host and share open ML datasets. It offers features such as support for large datasets and generous limits, making it a convenient solution for data-intensive projects.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 80 | 2024-11-12 05:50:32 PM |
Hugging Face has integrated its features into PyCharm, allowing users to access and utilize its functionality directly within the PyCharm environment.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 80 | 2024-11-05 03:00:48 PM |
Argilla has released a new version, 2.4, that allows users to build fine-tuning and evaluation datasets on the Hub without needing to write any code. Argilla is a data-centric tool part of the Hugging Face family, designed for AI developers and domain experts to collaborate and create high-quality datasets. The new feature enables users to import a dataset from the Hugging Face Hub, define questions, and collect human feedback using Argilla's UI.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 81 | 2024-11-04 02:50:33 PM |
Universal Assisted Generation is a new method that allows faster decoding from any decoder or Mixture of Experts model, even small ones. This was developed by Intel Labs and Hugging Face and can significantly accelerate inference.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 86 | 2024-10-29 12:28:45 PM |
There are 500 million smallholder farmers globally, who rely on timely access to accurate information to make informed decisions and improve their yields. An agricultural extension service provides technical advice and necessary inputs to support their production.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 90 | 2024-10-28 04:39:34 PM |
Hugging Face has partnered with Protect AI to enhance model security for the ML community. Protect AI's Guardian tool aims to address security concerns without hindering AI innovation. The partnership reflects Hugging Face's commitment to providing a safe and reliable platform.
Source: https://huggingface.co/blog
AIHuggingFace | Rating: 86 | 2024-10-25 03:39:36 PM |