executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
unslothUse 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
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.