ymcui/chinese-llama-alpaca

★ 18,946PythonAudience · developerComplexity · 3/5MaintainedLicenseSetup · hard

Mindmap

mindmap
  root((repo))
    What it does
      Chinese LLaMA base model
      Chinese Alpaca chat model
      Local deployment support
    Key features
      LoRA weight patches
      CPU and GPU compatible
      Multiple model sizes
    Use cases
      Run Chinese chatbot locally
      Text generation in Chinese
      Private data processing
    Tech stack
      Python
      LLaMA foundation
      LoRA fine-tuning
    Supported tools
      llama.cpp
      transformers
      LangChain

mindmap root((repo)) What it does Chinese LLaMA base model Chinese Alpaca chat model Local deployment support Key features LoRA weight patches CPU and GPU compatible Multiple model sizes Use cases Run Chinese chatbot locally Text generation in Chinese Private data processing Tech stack Python LLaMA foundation LoRA fine-tuning Supported tools llama.cpp transformers LangChain

Things people build with this

USE CASE 1

Run a Chinese-language chatbot on your laptop without cloud services or API costs.

USE CASE 2

Process sensitive Chinese text locally while keeping data private and offline.

USE CASE 3

Fine-tune or customize a Chinese language model for domain-specific tasks like customer support or content generation.

Tech stack

PythonLLaMALoRAllama.cpptransformersLangChain

Getting it running

Difficulty · hard Time to first run · 1h+

Requires downloading large model weights (7B-13B GB) and either GPU/CUDA setup or CPU inference which is slow.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

This project provides Chinese-language versions of the LLaMA and Alpaca large language models, AI systems capable of understanding and generating text. The core problem it solves: the original LLaMA model was primarily trained on English text, so its Chinese language ability was limited. This project takes LLaMA as a starting point, expands its vocabulary with Chinese characters, and then re-trains it on Chinese text data to dramatically improve its Chinese comprehension. Two model variants are offered. Chinese LLaMA is the base language model good at text completion, give it the start of a sentence and it generates the rest. Chinese Alpaca goes a step further by training with instruction-following data, making it behave more like a chat assistant (similar to ChatGPT) that can answer questions, write content, and follow directions in Chinese. A key practical feature is local deployment: you can run these models on a personal laptop using just the CPU or a consumer GPU, without sending data to any cloud service. The models are distributed as LoRA weights, a compact "patch" file that you merge with the original LLaMA model weights to get the full model. Supported tools include llama.cpp, transformers, text-generation-webui, LangChain, and privateGPT. Available in 7B, 13B, and 33B parameter sizes, written in Python.

Copy-paste prompts

Prompt 1

How do I download and set up Chinese LLaMA or Chinese Alpaca on my computer using the LoRA weights?

Prompt 2

Show me how to merge the LoRA weights with the base LLaMA model to create the full Chinese model.

Prompt 3

What's the difference between Chinese LLaMA and Chinese Alpaca, and which one should I use for a chatbot?

Prompt 4

How do I run Chinese Alpaca locally using llama.cpp or the transformers library?

Prompt 5

Can I use this Chinese LLaMA model with LangChain or privateGPT for my own application?

Open on GitHub → Explain another repo

Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.