计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
unsloth【效率与协作】Use Unsloth Core, CLI, Studio, and export workflows for fast LLM finetuning, local inference, Studio serving, and checkpoint conversion.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
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.
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.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.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.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.references/install-and-backends.md before advising installation, optional extras, hardware backends, Core-vs-Studio choices, or safe import checks.references/troubleshooting.md for cross-cutting install/import, optional dependency, CUDA/MLX/ROCm, network/cache, token, and routing failures.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.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.FastLanguageModel, get_peft_model, SFTTrainer, standardize_sharegpt, or dataset formats, route to core-training.unsloth train --dry-run, unsloth run, unsloth connect, or parser errors, route to cli-workflows.model-export.studio-runtime.transformers, trl, or peft in Python training scripts so its patches apply early.unsloth train --dry-run for CLI training config validation before any real training run.unsloth studio --secure for remote access; treat -H 0.0.0.0 as a raw network exposure that requires explicit risk acceptance.torch, unsloth_zoo, bitsandbytes, xformers, flash-attn, triton, llama.cpp, and Studio dependencies against the chosen workflow.