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Climate & Sustainability
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Climate & Sustainability
Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP
Algorithms & Theory
Migrating Your GitHub CI to Hugging Face Jobs
How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces
The Open Source Community is backing OpenEnv for Agentic RL
Health & Bioscience
Designing the hf CLI as an agent-optimized way to work with the Hub
Climate & Sustainability
Direct Preference Optimization Beyond Chatbots
Holo3.1: Fast & Local Computer Use Agents
Introducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains
Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler
Google’s research team has unveiled a new private analytics solution that leverages an innovative single-round lattice-based cryptographic aggregation protocol, working in tandem with a Trusted Execution Environment (TEE), to enable data aggregation without relying on any single trusted entity. This approach ensures that user data remains securely stored on the device while delivering group-level anonymized insights.
Published breakthroughs pushing the state of the art.
Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL
Reachy Mini goes fully local
Harness, Scaffold, and the AI Agent Terms Worth Getting Right