feat: CI support for tracing_finetuned_models - #21
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Make the guide run end-to-end in notebook CI (test-notebooks.yml) without a GPU or training: - Gate Section 1 (fine-tune + register) behind RUN_TRAINING (default off): CI and default runs skip training; set RUN_TRAINING=true locally to train on a GPU. - Section 2 loads base distilgpt2 from HuggingFace (USE_MODEL_REGISTRY off) and Section 3 traces inference to Opik — the live path CI exercises. - Rework the credentials cell: read OPIK_/COMET_ keys from the environment, only prompt in an interactive session (never in CI), and require Comet keys only when training or downloading from the registry. - Drop run.sh: notebook examples are run.sh-exempt and executed by test-notebooks.yml; a run.sh made the folder match both workflows (double run). Verified: `uv run ipython tracing_finetuned_models.ipynb` runs on CPU and exits 0 (Section 1 skipped, Section 2/3 trace). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Summary
run.sh— loadsdistilgpt2from HuggingFace by default so CI runs without CometML registry credentials; sends real traces to Opik whenOPIK_API_KEY+OPIK_WORKSPACEare setUSE_MODEL_REGISTRYenv var to explicitly opt in to downloading from the CometML Model Registry (requiresCOMET_API_KEY,COMET_WORKSPACE)use_registered_model.pyandtracing_finetuned_models.ipynbto use the new flag — registry metadata only attached to traces whenUSE_MODEL_REGISTRY=trueTest plan
OPIK_API_KEY+OPIK_WORKSPACE— traces visible in Opiklrb/ci-workflows🤖 Generated with Claude Code