Die Oberfläche ist lokalisiert; Skill-Beschreibungen und -Dokumente werden per KI automatisch in Ihre Sprache übersetzt. Code, Befehle, Pfade und Fachbegriffe bleiben im Original, maßgeblich ist das Dokument des Autors.
Skills entdecken
Produktivität · SKILL.md

unsloth

unsloth

Use Unsloth Core, CLI, Studio, and export workflows for fast LLM finetuning, local inference, Studio serving, and checkpoint conversion.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: unsloth description: "Use Unsloth Core, CLI, Studio, and export workflows for fast LLM finetuning, local inference, Studio serving, and checkpoint conversion." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Unsloth

Use this repo skill when a user asks about Unsloth, Unsloth Core, Unsloth Studio, the unsloth CLI, fast LoRA/QLoRA/full finetuning, GGUF or merged checkpoint export, local Studio/API serving, or connecting coding agents to an Unsloth Studio server.

Route First

  • Read sub-skills/core-training/SKILL.md for code-first Python workflows with FastLanguageModel, FastModel, FastVisionModel, LoRA/full finetuning, chat templates, raw-text/data checks, trainer setup, and backend/import troubleshooting.
  • Read sub-skills/cli-workflows/SKILL.md for unsloth train, inference, chat, export, list-checkpoints, studio, run, connect, YAML/JSON config dry-runs, pass-through flags, and CLI parser troubleshooting.
  • Read sub-skills/model-export/SKILL.md for adapter, merged, GGUF, Ollama, and Hub export planning, tokenizer/output preflight, unsloth_save_model, save_to_gguf, and export failures.
  • Read sub-skills/studio-runtime/SKILL.md for Unsloth Studio install/launch/update, secure tunnel vs raw host binding, backend APIs, providers, RAG/data recipes, tool policy, GGUF/llama.cpp runtime, and coding-agent connection.

Shared References

  • Read references/install-and-backends.md before advising installation, optional extras, hardware backends, Core-vs-Studio choices, or safe import checks.
  • Read references/troubleshooting.md for cross-cutting install/import, optional dependency, CUDA/MLX/ROCm, network/cache, token, and routing failures.
  • Read references/repo-provenance.md when deciding whether this skill is stale relative to the source repository.
  • references/repo-routing-metadata.json is structured metadata for DisCo import routing; future agents normally do not need to read it manually.

Shared Script

  • Run scripts/check_unsloth_environment.py --help to inspect installed package metadata, CLI availability, backend packages, and optional CUDA state without loading a model, downloading weights, starting Studio, or training.

Start With The User's Interface

  • If the user gives Python code, mentions FastLanguageModel, get_peft_model, SFTTrainer, standardize_sharegpt, or dataset formats, route to core-training.
  • If the user gives shell commands, YAML/JSON configs, unsloth train --dry-run, unsloth run, unsloth connect, or parser errors, route to cli-workflows.
  • If the user asks to save, merge, convert, quantize, upload, create GGUF, create an Ollama model, or list checkpoints, route to model-export.
  • If the user mentions the web UI, local API server, browser launch, Cloudflare tunnel, API key, providers, RAG, tool execution, llama.cpp, GGUF serving, or agent connection to Studio, route to studio-runtime.

Safe Defaults

  • Prefer planning and preflight checks before model downloads, long training, export conversion, Studio setup, or networked provider calls.
  • Import Unsloth before transformers, trl, or peft in Python training scripts so its patches apply early.
  • Use unsloth train --dry-run for CLI training config validation before any real training run.
  • Prefer unsloth studio --secure for remote access; treat -H 0.0.0.0 as a raw network exposure that requires explicit risk acceptance.
  • Keep tokens out of reusable files and logs; pass Hugging Face, W&B, Studio API, and provider credentials through environment variables or secure stores.
  • Do not assume every optional acceleration package is installed. Check torch, unsloth_zoo, bitsandbytes, xformers, flash-attn, triton, llama.cpp, and Studio dependencies against the chosen workflow.

What This Skill Does Not Cover

  • It does not reproduce Unsloth benchmarks, run long finetuning jobs, download gated models, push to the Hub, start Studio servers, or mutate user installs without explicit user approval.
  • It does not treat source repository tests, notebooks, examples, or install scripts as runtime dependencies; relevant behavior is distilled into bundled references and safe helper scripts.
  • It does not replace official Unsloth docs for model catalogs or notebook links; use public docs for live model availability and this skill for repo-specific API/CLI/runtime behavior.
Gespeicherte Skills