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Get Started Free →orchestra-research/experiment-tracking-swanlab
Provides guidance for experiment tracking with SwanLab.
Passed 22 of 22 test cases with the skill, and 13 of 22 without it.
and 12 more in the full report
9 fixed13 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
At the end of a standalone training script that initialized tracking with `run = swanlab.init(...)`, what method cleanly closes out the run and flushes remaining logged buffer data?
| Checked | Without skill | With skill |
|---|---|---|
| The script explicitly invokes run.finish(). | Missed | Passed |
The instructions your model reads when the skill loads.
Use SwanLab when you need to:
Deployment: Cloud, local, or self-hosted | Media: images, audio, text, GIFs, point clouds, molecules | Integrations: PyTorch, Transformers, PyTorch Lightning, Fastai
# Install SwanLab plus the media dependencies used in this skill
pip install "swanlab>=0.7.11" "pillow>=9.0.0" "soundfile>=0.12.0"
# Add local dashboard support for mode="local" and swanlab watch
pip install "swanlab[dashboard]>=0.7.11"
# Optional framework integrations
pip install transformers pytorch-lightning fastai
# Login for cloud or self-hosted usage
swanlab login
pillow and soundfile are the media dependencies used by the Image and Audio examples in this skill. swanlab[dashboard] adds the local dashboard dependency required by mode="local" and swanlab watch.
import swanlab
run = swanlab.init(
project="my-project",
test cases passed, vs 13 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.