README.md

---
license: apache-2.0
---
这是基于Auto-GPTQ框架的量化模型，模型选取为huatuoGPT2-7B,这是一个微调模型，基底模型为百川-7B。

参数说明：
原模型大小：16GB，量化后模型大小：5GB

推理准确度尚未测试，请谨慎使用

量化过程中，校准数据采用微调训练集Medical Fine-tuning Instruction (GPT-4)。

使用示例：

确保你安装了bitsandbytes
```
pip install bitsandbytes
```

确保你安装了auto-gptq
!git clone https://github.com/AutoGPTQ/AutoGPTQ
cd AutoGPTQ
!pip install -e .

```
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation.utils import GenerationConfig
tokenizer = AutoTokenizer.from_pretrained("jiangchengchengNLP/huatuo_AutoGPTQ_7B4bits", use_fast=True, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("jiangchengchengNLP/huatuo_AutoGPTQ_7B4bits", device_map="auto", torch_dtype="auto", trust_remote_code=True)
model.generation_config = GenerationConfig.from_pretrained("jiangchengchengNLP/huatuo_AutoGPTQ_7B4bits")
messages = []
messages.append({"role": "user", "content": "肚子疼怎么办？"})
response = model.HuatuoChat(tokenizer, messages)
print(response)


```
更多量化细节：

量化环境：双卡T4

校正规模：512 训练对

量化配置：
```
ntize_config = BaseQuantizeConfig(
    bits=4, # 4 or 8
    group_size=128,
    damp_percent=0.01,
    desc_act=False,  # set to False can significantly speed up inference but the perplexity may slightly bad
    static_groups=False,
    sym=True,
    true_sequential=True,
    model_name_or_path=None,
    model_file_base_name="model"
)
```