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README.md

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 # 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. 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.
+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](https://huggingface.co/datasets/mbpp), we calculated the compression rate of the tokenizer to be 38.59%.
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+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.