Chinese-LLaMA-Alpaca-2

This skill routes work for the Chinese-LLaMA-2 and Chinese-Alpaca-2 repository. It is intentionally a router, not a full manual.

Use it when a task mentions:

• Chinese-LLaMA-2 or Chinese-Alpaca-2 model paths, tokenizers, or prompts
• pretraining, SFT, LoRA merging, or model conversion
• local generation, Gradio chat, speculative sampling, or long-context helpers
• OpenAI-compatible serving, HTTP endpoints, or deployment wrappers
• C-Eval, CMMLU, LongBench, or benchmark result files
• llama.cpp launch wrappers or the repo's retrieval-style integration notes

Pick a sub-skill

Task family	Read
Dataset prep, pretraining, SFT, or merge/export	sub-skills/train-and-merge/SKILL.md
Transformers inference, chat UI, speculative sampling, or prompt wrapping	sub-skills/hf-inference/SKILL.md
OpenAI-style API serving or the FastAPI server	sub-skills/api-serving/SKILL.md
C-Eval, CMMLU, or LongBench evaluation	sub-skills/evaluation/SKILL.md
llama.cpp wrappers or external integration notes	sub-skills/local-integrations/SKILL.md

Bundled assets

• assets/prompts/alpaca-2.txt
• assets/prompts/alpaca-2-long.txt
• assets/tokenizer/

Read references/prompt-and-tokenizer.md before changing prompt text or tokenizer assumptions.

Cross-cutting references

• references/workflows.md for the repository's main workflow map
• references/model-overview.md for model family, context, and backend compatibility guidance
• references/troubleshooting.md for shared failure modes
• references/repo-provenance.md for source commit and staleness checks
• references/repo-routing-metadata.json for router import metadata

Router behavior

• Prefer the most specific sub-skill.
• Use the training sub-skill for data preparation or merge/export questions even when the task also mentions inference.
• Use the inference sub-skill for local generation or chat UX questions even when the task mentions prompt templates.
• Use the API-serving sub-skill for OpenAI-compatible HTTP responses, request schemas, or deployment flags.
• Use the evaluation sub-skill for benchmark configuration and result files, not for general model comparison prose.
• Use the local-integrations sub-skill for llama.cpp wrappers and the external integration notes around retrieval-style examples.

Notes

• The generated runtime skill is self-contained; do not rely on the source checkout staying available.
• If a task needs more detail than this router provides, open the nearest references/*.md file instead of widening the router itself.