Fix qwen3-0.6b LoRA training example - #74
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Each README links to Baseten signup, walks through `truss train init`, `cd`, and `truss train push`, and notes when instance types (>H100:4 or any H200) require contacting Baseten for approval. Also moves qwen3-235b-mswift files into a training/ subdirectory to match the standard example structure expected by the SDK. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
truss train init flattens the training/ contents into the example directory, so after cd the config.py is at the root level. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…rs+peft+trl The axolotl Docker image copies artifacts to /workspace/axolotl which overwrites the editable axolotl install, breaking all axolotl imports. Replaced with a pytorch base image using SFTTrainer from TRL with LoRA via PEFT. Also switched GPU from H100 to H200 and pinned all dependencies (trl==0.29.0, peft==0.18.1, datasets==4.6.0). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
pytorch/pytorch:2.7.0-cuda12.8-cudnn9-runtimebase imageSFTTrainerfrom TRL + LoRA via PEFT instead of axolotl (the axolotl image's editable install at/workspace/axolotlgets overwritten by artifact copy)trl==0.29.0,peft==0.18.1,datasets==4.6.0Test plan
wd14xmwon Baseten production — completed successfully in ~10s🤖 Generated with Claude Code