Chinese-LLaMA-2: Accelerating Chinese NLP with LLaMA and Alpaca Models
Expanding to the Chinese Language
MetaAI's Llama-2 language model has demonstrated remarkable capabilities. The Chinese-Llama-2 project aims to bring these capabilities to the Chinese language. By extending Llama-2's vocabulary and leveraging Chinese-LLaMA-2-13B and Chinese-Alpaca-2-13B models, the project aims to accelerate inference speed.
Enhancing Vocabulary and Semantic Understanding
This project augments LLaMA with the ability to understand and generate Chinese text effectively. By expanding its vocabulary with an additional 20,000 Chinese tokens, the model's encoding efficiency and semantic understanding of Chinese have been significantly improved.
Inference Speed Optimization
Speculative sampling techniques are employed to optimize Chinese-LLaMA-2 models, resulting in improved inference speed for 7B and 13B LLaMA and Alpaca models. The project demonstrates these enhancements through performance evaluations on Generation Performance Evaluation on 1A40-48G.
Open-Source Availability
The core components of this project are open-sourced, including the Chinese LLaMA-2 and Alpaca-2 LLMs. This allows researchers and developers to utilize and extend these models for a wide range of applications.
Additional Features
The project also includes: * A new extended Chinese vocabulary beyond Llama-2 * GGUF format model files for Chinese-Llama-2-7B * A Chinese instruction fine-tuned version of llama2-7B-HF * Support for 4K context, expandable to 18K using the NTK method * Chinese-LLaMA-2 Alpaca-2 LLMs with 64K long context models
Conclusion
The Chinese-Llama-2 project represents a significant contribution to the advancement of Chinese NLP. By enhancing the capabilities of Llama-2 for the Chinese language and providing open-source access to the models, this project empowers researchers and developers to drive further innovation and facilitate the development of Chinese-language AI solutions.
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