This project has open sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA, these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which significantly improves the model's ability to understand and execute instructions.
Technical Report (V2): [Cui, Yang, and Yao] Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca 👐🏻🧥🚀ExpandedtheChinesevocabularyfortheoriginalLLaMAmodel,improvingtheefficiencyofChineseencodinganddecodingWithpre-trainingscriptsandinstructionfine-tuningscripts,userscanfurthertrainthemodelasneededllama.cpp,text-generation-webui,LlamaChat,LangChain,privateGPTandotherecological Currentlyopensourcemodelversions:7B(Basic,Plus,Pro),13B(Basic,Plus,Pro),33B(basicversion,Plusversion,Proversion) 💡ThepicturebelowshowstheactualexperiencespeedandeffectoftheChineseAlpaca-Plus-7BmodelafterthelocalCPUquantitativedeployment.
Chinese LLaMA-2&Alpaca-2 Mockup \| Multimodal Chinese LLaMA&Alpaca Mockup \| Multimodal VLE \| Chinese MiniRBT \| Chinese LERT \| Chinese and English PERT \| Chinese MacBERT \| Chinese ELECTRA \| Chinese XLNet \| Chinese BERT \| Knowledge Distillation Tool TextBrewer \| Model Cutting Tool TextPruner
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