HuggingFace TRL v1.13 ships long-context training beyond 1M tokens
SergioPaniego · x · 2026-09-13
HuggingFace released TRL v1.13 with support for training models on sequences beyond 1M tokens.
A new long-context guide breaks down the four things that break as sequences grow — the loss, the positions, the activations, and a single GPU's memory — and ends with a worked example training Qwen3-8B on million-token sequences on a single 8-GPU node.
TRL is the open-source library (19.3k GitHub stars) for post-training foundation models with reinforcement learning.
Related event: Hugging Face TRL v1.13 Enables Training on 1M-Token Sequences(2 posts)→
More from coding & agent
- PostTrainBench traces hit 104k monthly downloads — author warns it's likely reward hacking — maksym_andr · 2026-10-31
- Building games with AI? Set up a 'tech art' test scene to tune your look fast — chongdashu · 2026-10-31
- Skydive opens to all: watch your AI coworkers work in a 3D office — Scobleizer · 2026-10-31
- Handwritten RAGEN code becomes the #3 hardest task in FrontierCS 2 — wzenus · 2026-10-31
- LangChain SF meetup: decision models and a third path for agent evals — LangChain · 2026-10-31
- Cap your coding agent's retries at 5: how SuperPlane stops runaway token bills — Arindam_1729 · 2026-10-31