Text Generation
Transformers
PyTorch
Chinese
English
llama
text-generation-inference
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@@ -18,6 +18,8 @@ baichuan-vicuna-7b is a chat model supervised finetuned on vicuna sharegpt data.
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  [中文说明](#chinese-model-card)
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  # Load model
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
@@ -124,7 +126,7 @@ This algorithm has a runtime complexity of O(log n) and a space complexity of O(
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  baichuan-vicuna-7b是在vicuna sharegpt数据上全参数微调的对话模型。
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  - 基座模型是[baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B),由百川智能开发的可商用大规模预训练模型。
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  - 微调数据包括[ShareGPT](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split.json),混合一定比例的[COT](https://huggingface.co/datasets/QingyiSi/Alpaca-CoT)和[Leetcode](https://www.kaggle.com/datasets/erichartford/leetcode-solutions)数据以提升模型的推理和代码能力(数据混合策略受到[TULU](https://arxiv.org/abs/2306.04751)研究成果的启发)。
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- - 训练代码在https://huggingface.co/fireballoon/baichuan-vicuna-7b/blob/main/train_vicuna.py, 代码基于[FastChat](https://github.com/lm-sys/FastChat)。
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  # Test examples on Ziyan Eval
 
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  [中文说明](#chinese-model-card)
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+ **[New]** [baichuan-vicuna-chinese-7b](https://huggingface.co/fireballoon/baichuan-vicuna-chinese-7b), baichuan finetuned on both English and Chinese ShareGPT.
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+
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  # Load model
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
 
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  baichuan-vicuna-7b是在vicuna sharegpt数据上全参数微调的对话模型。
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  - 基座模型是[baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B),由百川智能开发的可商用大规模预训练模型。
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  - 微调数据包括[ShareGPT](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/blob/main/ShareGPT_V3_unfiltered_cleaned_split.json),混合一定比例的[COT](https://huggingface.co/datasets/QingyiSi/Alpaca-CoT)和[Leetcode](https://www.kaggle.com/datasets/erichartford/leetcode-solutions)数据以提升模型的推理和代码能力(数据混合策略受到[TULU](https://arxiv.org/abs/2306.04751)研究成果的启发)。
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+ - 训练代码:https://huggingface.co/fireballoon/baichuan-vicuna-7b/blob/main/train_vicuna.py, 代码基于[FastChat](https://github.com/lm-sys/FastChat)。
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  # Test examples on Ziyan Eval