Halo: A New Post-Training Framework for Open-Source Models with 2.8x Throughput

Key Info

Hugging Face introduces Halo, a new framework for post-training open-source models, claiming up to 2.8x throughput compared to stock TRL while using less peak memory and keeping models in native HuggingFace format.

Highlights

• Halo is a framework for post-training open-source models, emphasizing support for agents.
• Achieves up to 2.8x throughput over stock TRL with reduced peak memory usage.
• Models remain in their native HuggingFace format throughout the process.
• Available as an open-source project on GitHub.