Facico/Chinese-Vicuna

Health v2 · maintenance only

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4113 stars · 405 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Chinese-Vicuna is a low-resource LLaMA+LoRA solution for building Chinese instruction-following language models, structured after Alpaca. It provides fine-tuning, generation, and CPU inference code that can train LLaMA-7B on a single RTX 2080Ti and multi-round chatbots on a single RTX 3090.

Use cases

• fine-tune llama on chinese instruction data with a single consumer gpu
• train a chinese multi-round chatbot on a 3090
• run a llama-based chinese model on cpu with int4 quantization
• adapt llama to a chinese domain like medical or legal text
• convert and quantize original facebook llama checkpoints
• train llama 13b with qlora 4-bit on an 11gb gpu

When to choose

• you need a chinese instruction-tuned llama on limited gpu memory
• you want parameter-efficient lora/qlora fine-tuning of llama
• you need cpu-only inference of a llama model in c++

When to avoid

• you need a state-of-the-art multilingual model rather than a llama-era fine-tune
• you want a managed api instead of self-hosted training and inference
• you need languages other than chinese

Facets

library · maturity maintenance

llm-training llm-inference chatbot machine-learning large-language-models machine-learning artificial-intelligence python cpp llama lora qlora chinese-nlp instruction-tuning fine-tuning low-resource alpaca natural-language-processing gpu linux

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