overthinkos/python-ml
ov-images/skills/python-ml/SKILL.md
GPU-accelerated Python ML environment with CUDA, PyTorch, and llama.cpp. No Jupyter server — use as a base for ML workloads or interactive shell. MUST be invoked before building, deploying, configuring, or troubleshooting the python-ml image.
development
Updated Apr 24, 2026
$ install --global
skillsauthnpx skillsauth add overthinkos/overthink-plugins python-mlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- python-ml
- description:
- |
python-ml
GPU-accelerated Python environment with ML libraries — PyTorch, transformers, vLLM, llama.cpp.
Image Properties
| Property | Value | |----------|-------| | Base | nvidia | | Layers | agent-forwarding, python-ml | | Platforms | linux/amd64 | | Registry | ghcr.io/overthinkos |
Layer Composition
The python-ml layer is a Tier 2 environment-owner meta-layer that:
- Owns the pixi.toml (core ML Python environment)
- Composes
llama-cpp(Tier 1 sub-layer) vialayers: [llama-cpp] - Installs vLLM 0.19 wheel via a cmd task (after pixi env is established)
Build order: pixi environment → llama-cpp (binaries) → vLLM 0.19 wheel
Full Layer Stack
fedora→nvidia(CUDA base)pixi→python(transitive)python-ml— ML pixi environment (Tier 2, owns pixi.toml)llama-cpp— llama.cpp binaries (Tier 1, vialayers:field)
Quick Start
ov image build python-ml
ov shell python-ml
# python -c "import torch; print(torch.cuda.is_available())"
Key Layers
/ov-layers:python-ml— ML Python packages via pixi (Tier 2 meta-layer)/ov-layers:llama-cpp— llama.cpp binaries (sub-layer)/ov-layers:cuda— GPU support (via nvidia base)
Related Images
/ov-images:nvidia— parent (GPU without ML packages)/ov-images:jupyter-ml— adds JupyterLab + collaboration + MCP + unsloth on top of ML stack/ov-images:jupyter— legacy Jupyter with ML stack (monolithic)/ov-images:unsloth-studio— fine-tuning UI with similar ML stack
Verification
After ov image build:
ov shell python-ml -c "python -c 'import torch; print(torch.cuda.is_available())'"— CUDA OKov shell python-ml -c "python -c 'import vllm; print(vllm.__version__)'"— vLLM OKov shell python-ml -c "ls ~/llama.cpp/llama-quantize"— llama.cpp OK
When to Use This Skill
MUST be invoked when the task involves the python-ml image, ML training environments, or GPU-accelerated Python. Invoke this skill BEFORE reading source code or launching Explore agents.
Related
/ov:image— image family umbrella (image:entries inoverthink.yml, build/validate/inspect/list)/ov:build—build.ymlvocabulary (distros, builders, init-systems)
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