We are incredibly excited to welcome the next generation of large language models from Meta to the Hugging Face Hub: Llama 4 Maverick (~400B) and Llama 4 Scout (~109B)! 🤗 Both are Mixture of Experts (MoE) models with 17B active parameters. Released today, these powerful, natively multimodal models represent a significant leap forward. We’ve worked closely with Meta to ensure seamless integration into the Hugging Face ecosystem, including both transformers and TGI from day one. This is just the start […]

At Inception, we have been working to enhance AI model evaluations within the Arabic language context. Previously, we introduced AraGen, one of the first generative Arabic leaderboards, serving as a benchmark for evaluating Arabic LLMs on generative tasks. As part of our ongoing efforts, we are excited to share the following updates: Arabic-Leaderboards Space, launched in collaboration with Mohammed bin Zayed University of Artificial Intelligence (MBZUAI) to consolidate Arabic AI evaluations in one place. This platform currently supports AraGen-03-25 and […]

We’re excited to announce a new partnership between Cloudflare and Hugging Face that gives FastRTC developers instant access to enterprise-grade WebRTC infrastructure with a Hugging Face token. As a preview of what you can build with FastRTC and Cloudflare, check out this voice chat app built with Meta’s new Llama 4 model!

The Language Technologies Lab takes a major step forward in multimodal artificial intelligence with the release of Visual Salamandra, extending the capabilities of the Salamandra large language    

Hugging Face and Protect AI partnered in October 2024 to enhance machine learning (ML) model security through Guardian’s scanning technology for the community of developers who explore and use models from the Hugging Face Hub. The partnership has been a natural fit from the start—Hugging Face is on a mission to democratize    

Simon Alibert and Rémi Cadène from the LeRobot team with Reachy 1 — Photo: Léa Crespi Since Hugging Face started the LeRobot library in 2024, led by ex-Tesla lead Remi Cadene, the Hugging Face Hub has quickly become the most widely used hub and software platform for open robotics with models, datasets, spaces and libraries. Today, we’re excited to take it a step further by welcoming Pollen Robotics to Hugging Face, a team that’s spent the last 9 years building […]

Contact: hyen@cs.princeton.edu Paper: https://arxiv.org/abs/2410.02694 Website: https://princeton-nlp.github.io/HELMET Code & Data: https://github.com/princeton-nlp/HELMET Since we first released HELMET last October, there has been more development on long-context language models than ever before, and we are thrilled to see the adoption of HELMET by the community, such as Microsoft’s Phi-4 and AI21’s Jamba 1.6. After the initial release, we have added more models to our evaluation suite and conducted additional analyses. We are excited to share our new results and present HELMET at ICLR […]

We’re thrilled to share that Cohere is now a supported Inference Provider on HF Hub! This also marks the first model creator to share and serve their models directly on the Hub. Cohere is committed to building and serving models purpose-built for enterprise use-cases. Their comprehensive suite of secure AI solutions, from cutting-edge Generative AI to powerful Embeddings and Ranking models, are designed to tackle real-world business challenges. Additionally, Cohere Labs, Cohere’s in house research lab, supports fundamental research and […]

“Oh, Gradio? That’s a Python library for building UIs, right?” We hear this a lot, and while Gradio does let you create interactive UIs with minimal Python code, calling Gradio a “UI library” misses the bigger picture! Gradio is    

Handling load from multiple users in parallel is crucial for the performance of LLM applications. In the previous part of our series on LLM performance, we discussed queueing strategies for the prioritization of different users. In this second part, we will now focus on the concurrent processing of requests, and how it impacts relevant metrics such as latency