模型量化
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模型量化
模型量化
飞书用户8537
飞书用户7960
飞书用户7022024年2月23日修改
对中文微调的模型参数进行了量化，方便以更少的计算资源运行。目前已经在Hugging Face上传了13B中文微调模型FlagAlpha/Llama2-Chinese-13b-Chat的4bit压缩版本FlagAlpha/Llama2-Chinese-13b-Chat-4bit，具体调用方式如下：
环境准备：
代码块
pip install git+https://github.com/PanQiWei/AutoGPTQ.git
代码块
from transformers import AutoTokenizer
from auto_gptq import AutoGPTQForCausalLM
model = AutoGPTQForCausalLM.from_quantized('FlagAlpha/Llama2-Chinese-13b-Chat-4bit', device="cuda:0")
tokenizer = AutoTokenizer.from_pretrained('FlagAlpha/Llama2-Chinese-13b-Chat-4bit',use_fast=False)
input_ids = tokenizer(['<s>Human: 怎么登上火星\n</s><s>Assistant: '], return_tensors="pt",add_special_tokens=False).input_ids.to('cuda')
generate_input = {
"input_ids":input_ids,
"max_new_tokens":512,
"do_sample":True,
"top_k":50,
"top_p":0.95,
"temperature":0.3,
"repetition_penalty":1.3,
"eos_token_id":tokenizer.eos_token_id,
"bos_token_id":tokenizer.bos_token_id,
"pad_token_id":tokenizer.pad_token_id
}
generate_ids = model.generate(**generate_input)
text = tokenizer.decode(generate_ids[0])
print(text)