代码与脚本 Code and Scripts

training/

预训练与指令精调代码，Wiki：

• 预训练：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/预训练脚本
• 指令精调：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/指令精调脚本

Pre-training and instruction finetuning code, Wiki:

• Pre-training: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Pretraining-Script
• Instruction finetuning: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/SFT-Script

inference/

使用🤗transformers进行推理，Wiki：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/使用Transformers推理

Inference using 🤗transformers, Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Inference-with-Transformers

langchain/

使用LangChain进行检索式问答和文本摘要的示例，Wiki：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/与LangChain进行集成

Using LangChain for Retrieval QA and Summarization, Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Integrated-with-LangChain

openai_server_demo/

使用fastapi实现的仿OPENAI API风格的服务器，Wiki：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/API调用

A server that implements OPENAI API using fastapi, Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/API-Calls

merge_tokenizer/

中文词表扩充代码，Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/训练细节#准备工作词表扩充

Code for extending Chinese vocabulary, Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Training-Details#preparation-vocabulary-expansion

merge_llama_with_chinese_lora.py

合并LLaMA/Alpaca LoRA脚本，Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/手动模型合并与转换

Script for merging LLaMA/Alpaca LoRA. Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Manual-Conversion

merge_llama_with_chinese_lora_low_mem.py

（推荐）低资源版合并LLaMA/Alpaca LoRA脚本，Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/手动模型合并与转换

（recommended）Script for merging LLaMA/Alpaca LoRA (low-resource version). Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Manual-Conversion

crawl_prompt.py

指令数据爬取脚本，Wiki：https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/训练细节#训练数据

Crawl prompt script, Wiki: https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/Training-Details#training-data