license: apache-2.0
language:
- zh
- en
tags:
- code
Chinese-CodeLlama-7B-PT
We have further expanded the vocabulary based on Chinese-LLaMA-2-7B which from 55296 to 75548, it is worth noting that the most of them are code tokens. On MBPP, we calculated the compression rate of the tokenizer to be 38.59%.
We pre-trained the model based on LoRA which the rank is 8 and the trainable LoRA layers contain q_proj and v_proj, at the same time, embed_tokens and lm_head layers were trained with full parameters. All trainable parameters are float32.
The training data contains approximately 400 million tokens which from high-quality code dataset on HuggingFace.
In addition, we applied memory_efficient_attention to the pre-training, which saves us a lot of GPU memory space. If you want to quickly use this technology in your LLaMA model, you can refer to my GitHub: https://github.com/FrankMinions/memory_efficient_adapter.
Our model can be used for SFT, and we hope to contribute more valuable work in the Chinese field.