The team at WRITER is thrilled to announce the release of three new open models in the Palmyra-mini family. These models are designed to be powerful, lightweight, and highly performant for their size (1.5B to 1.7B),    

Last year, we shared a blogpost on watermarking, explaining what it means to watermark generative AI content, and why it’s important. The need for watermarking has become even more critical as people all over the world have begun to generate and share AI-generated images, video, audio, and text. Images and video have become so realistic    

TL;DR Today we release LeRobotDataset:v3! In our previous LeRobotDataset:v2 release, we stored one episode per file, hitting file-system limitations when scaling datasets to millions of episodes. LeRobotDataset:v3 packs multiple episodes in a single file, using relational metadata to retrieve information at the individual episode level from multi-episode files. The new format also natively supports accessing datasets in streaming mode, allowing to process large datasets on the fly.We provide a one-liner util to convert all datasets in the LeRobotDataset format to […]

We’re thrilled to share that Public AI is now a supported Inference Provider on the Hugging Face Hub! Public AI joins our growing ecosystem, enhancing the breadth and capabilities of serverless inference directly on the Hub’s model pages. Inference Providers are also seamlessly integrated into our client SDKs (for both JS and Python), making it super easy to use a wide variety of models with your preferred providers. This launch makes it easier than ever to access public and sovereign […]

Building trust in the open model ecosystem through standardized risk assessment More than 500,000 models can be found on the Hugging Face hub, but it’s not always clear to users how to choose the best model for them, notably on the security aspects. Developers might find a model that perfectly fits their use case, but have no systematic way to evaluate its    

We’re thrilled to share that Scaleway is now a supported Inference Provider on the Hugging Face Hub! Scaleway joins our growing ecosystem, enhancing the breadth and capabilities of serverless inference directly on the Hub’s model pages. Inference Providers are also seamlessly integrated into our client SDKs (for both JS and Python), making it super easy to use a wide variety of models with your preferred providers. This launch makes it easier than ever to access popular open-weight models like gpt-oss, […]

In an ideal world, AI agents would be reliable assistants. When given a query, they would easily manage ambiguity in instructions, construct step-by-step plans, correctly identify necessary resources, execute those plans without getting sidetracked, and adapt to unexpected events, all while maintaining accuracy and avoiding hallucinations. However, developing agents and testing these behaviors is no small feat: if you have ever tried to debug your own agent, you’ve probably observed how tedious and frustrating this can be. Existing evaluation environments […]

When we think about building a model - be it a Large Language Model (LLM) or a Small Language Model (SLM) - the first thing we need is data. While a vast amount of open data is available, it rarely comes in the exact format required to train or align models. In practice, we often face scenarios where the raw data isn’t enough. We need data that is more structured, domain-specific, complex, or aligned with the task at hand. Let’s look at some common […]

TL;DR: This work shows how a lightweight vision–language model can acquire GUI-grounded skills and evolve into an agentic GUI coder. We release all training recipes, data-processing tools, resulting model, demo and datasets to enable full reproducibility and foster further research 🫡. Find the collection here. This video demonstrates the model obtained through the recipe described below, executing a task end-to-end. Table of Contents

We released swift-transformers two years ago (!) with the goal to support Apple developers and help them integrate local LLMs in their apps. A lot has changed since then (MLX and chat templates did not exist!), and we’ve learned how the community is actually using the library. We want to double down on the use cases that provide most benefits to the community, and lay out the foundations for the future. Spoiler alert: after this release, we’ll focus a lot […]