llamafactory
Fine-tune LLMs with LlamaFactory — register datasets, train via YAML configs, merge LoRA adapters and serve the result.
npx skills add Prism-Shadow/penguin-harness --skill llamafactory --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LlamaFactory Fine-Tuning LlamaFactory fine-tunes open-weight LLMs (LoRA/QLoRA and full-parameter; SFT, DPO and more) through the `llamafactory-cli` command driven by YAML configs. ## Before you start If the user's message only invokes this skill (e.g. "use llamafactory skill") without a concrete request, ask the user what they want to fine-tune. Do not run any command until the goal is clear. Confirm before training: - GPU memory (`nvidia-smi`) — it bounds the model size and method; LoRA needs far less than full fine-tuning. - The base model: a Hugging Face id or a local path. - The dataset: where it lives and which format it is in. - The goal: SFT with LoRA is the usual starting point. ## Install ```bash git clone --depth 1 https://github.com/hiyouga/LlamaFactory.git cd LlamaFactory pip install -e . pip install -r requirements/metrics.txt # optional: evaluation metrics ``` ## Data Register every dataset in `data/dataset_info.json`; the alpaca and sharegpt formats are supported. A minimal local entry: ```json "my_dataset": { "file_name": "my_dataset.json" } ``` alpaca rows carry `instruction` / `input` / `output`; sharegpt rows carry a `conversations` list. Put the data file unde
- Before you start
- Install
- Data
- Train
- Merge and export
- Try the result
- Close the loop
git clone --depth 1 https://github.com/hiyouga/LlamaFactory.git cd LlamaFactory pip install -e . pip install -r requirements/metrics.txt # optional: evaluation metrics llamafactory-cli train my_sft.yaml llamafactory-cli export my_merge.yaml llamafactory-cli chat my_infer.yaml # interactive chat with the tuned model llamafactory-cli api my_infer.yaml # OpenAI-compatible API server
What does the llamafactory skill do?
Fine-tune LLMs with LlamaFactory — register datasets, train via YAML configs, merge LoRA adapters and serve the result.
How do I install it?
Run `npx skills add Prism-Shadow/penguin-harness --skill llamafactory --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Prism-Shadow/penguin-harness, a repository with 473 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.