docker-ml
Skill0 starsChanged 5 months agoNo licenceView on GitHub
Methodology for building, debugging, and editing Docker images for ML and scientific computing — especially GPU-enabled containers running PyTorch / TensorFlow / JAX, dependency resolution between framework CUDA wheels, NVIDIA Container Toolkit setup, image-size diagnosis, and Linux-vs-Mac bind-mount behavior. Use this skill whenever the user mentions Dockerfile, docker build, docker run, GPU passthrough, --gpus all, nvidia-container-toolkit, base images like nvidia/cuda, container CUDA versions, image bloat, wheel conflicts (especially tensorflow[and-cuda] vs torch), Jupyter-in-Docker, read-only bind mounts, UID mismatches, or anything else container-related. Also trigger when the user asks to fix, modify, simplify, or trim a Dockerfile, even if "docker" isn't mentioned explicitly — for any block-level edit to a Dockerfile, this skill defines the output convention (always return the entire RUN block, never a snippet).
In this repository6 other files it gives its agents.
- camb-devSkill
- cosmolike-devSkill
- cpp-loop-optimizationSkill
- explaining-codeSkill
- porting-legacy-physics-codeSkill
- pytorch-teaching-notebook-styleSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 4 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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