AI Briefing#huggingface
The latest AI and developer news about #huggingface, with the original source and a short summary.
The latest AI and developer news about #huggingface, with the original source and a short summary.
This analyzes the technical causes behind the differences in MMLU benchmark scores between the Open LLM Leaderboard and model papers.
With Panel templates on Hugging Face Spaces, you can easily build and deploy data dashboards and apps.
Hugging Face submitted a response to the US NTIA's request for comments on AI accountability, emphasizing transparency and multidisciplinary engagement.
HuggingFace has announced a new content policy for the responsible development of AI models and datasets.
Elixir-based Livebook notebooks can now be deployed as apps on Hugging Face Spaces.
Hugging Face and AMD have formed a partnership to optimize transformer model performance on AMD CPUs and GPUs.
Hugging Face has expanded the evaluation methodology of the Open LLM Leaderboard to verify the reliability of LLMs for data labeling.
A new feature has been added that allows datasets on Hugging Face Hub to be analyzed directly with SQL via DuckDB.
Meta AI's fastText models and word vectors for 157 languages have been integrated into the Hugging Face Hub.
The high-performance open-source LLM Falcon series developed by TII has been released into the Hugging Face ecosystem.
Hugging Face has launched a TGI-based LLM inference container dedicated to Amazon SageMaker.
Hugging Face and Microsoft have partnered to integrate the Hugging Face model catalog into Azure Machine Learning.
Thanks to 4-bit quantization and QLoRA technology, large language models can now be efficiently fine-tuned even with limited memory.
This introduces an instruction-tuning methodology that enables Stable Diffusion to understand and carry out users' image editing instructions.
The Safetensors library is establishing itself as the default format for model storage after proving its safety through an external security audit.
Hugging Face and IBM announced a collaboration for building enterprise AI through watsonx.ai.
RWKV, a new architecture that combines the efficiency of Transformer with the advantages of RNN, has been released.
Hugging Face has been selected for the French data protection authority (CNIL)'s AI data protection support program.
It introduces a new decoding technique that reduces text generation latency by up to 10x by solving the memory bandwidth problem, a bottleneck in LLM inference.
Introduces how to fine-tune StarCoder with ChatML and DeepSpeed to build the conversational coding assistant StarChat.
Hugging Face and ServiceNow collaborated to release StarCoder, a high-performance open-source code LLM.
Databricks and Hugging Face have launched a feature that directly converts Spark dataframes into Hugging Face datasets.
Hugging Face has launched a dedicated Chinese-language blog to collaborate with the Chinese AI community.
Hugging Face now supports AWS Inferentia2 optimization, improving inference performance and cost efficiency for Transformers models.