overthinkos/unsloth-studio
ov-layers/skills/unsloth-studio/SKILL.md
Unsloth Studio fine-tuning web UI on ports 8888/8000 with vLLM inference. Tier 2 environment-owner meta-layer composing llama-cpp + unsloth, owns pixi.toml. Use when working with Unsloth Studio, the fine-tuning web UI, or the unsloth-studio image.
development
Updated Apr 24, 2026
$ install --global
skillsauthnpx skillsauth add overthinkos/overthink-plugins unsloth-studioInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- unsloth-studio
- description:
- |
unsloth-studio -- Fine-tuning Studio (Tier 2 meta-layer)
Layer Properties
| Property | Value |
|----------|-------|
| Dependencies | cuda, supervisord |
| Sub-layers | llama-cpp, unsloth |
| Ports | 8888 (Studio UI), 8000 (vLLM API) |
| Volumes | workspace -> ~/workspace |
| Service | unsloth-studio (supervisord) |
| Install files | layer.yml, pixi.toml |
Architecture: Tier 2 Environment-Owner Meta-Layer
This layer owns the pixi.toml for the fine-tuning environment and composes two Tier 1 layers via layers: [llama-cpp, unsloth]. Build order: pixi environment → llama-cpp (binaries) → unsloth (vLLM wheel + unsloth pip + patch) → supervisord config.
Environment Variables
| Variable | Value |
|----------|-------|
| NVIDIA_PYTHON_PROJECT | ~/.pixi |
| LD_LIBRARY_PATH | /usr/lib64:$HOME/llama.cpp |
Plus from sub-layers: LLAMA_CPP_PATH, UNSLOTH_SKIP_LLAMA_CPP_INSTALL, HF_HOME
Packages (pixi.toml)
Fine-tuning focused ML stack: PyTorch (CUDA 13.0), xformers, transformers, accelerate, vLLM runtime deps, HuggingFace (datasets, tokenizers, sentencepiece), fine-tuning (peft, trl, bitsandbytes, liger-kernel), GGUF tools
Service
Runs pixi run start-studio which executes unsloth studio -H 0.0.0.0 -p 8888. The Studio launches its own vLLM API server on port 8000 for inference and synthetic data generation.
Used In Images
/ov-images:unsloth-studio
Related Layers
/ov-layers:llama-cpp— Sub-layer: llama.cpp binaries/ov-layers:unsloth— Sub-layer: vLLM + unsloth pip install + patch/ov-layers:supervisord— Process manager dependency/ov-layers:jupyter-ml— Alternative: ML Jupyter with MCP (same Tier 1 sub-layers)/ov-layers:python-ml— Alternative: core ML without UI
When to Use This Skill
Use when the user asks about:
- Unsloth Studio web UI setup
- The unsloth-studio service or container
- Port 8888 or 8000 in the context of fine-tuning
- The two-tier layer architecture for ML layers
- Fine-tuning pixi environment ownership
Related
/ov:layer— layer authoring reference (layer.ymlschema, task verbs, service declarations)/ov:test— declarative testing (tests:block,ov image test,ov test)
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