原项目见 [https://huggingface.co/baichuan-inc/Baichuan-13B-Chat]
改动点：将原模型量化为8bit 保存为2GB大小的切片。
使用方式(int8)
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation.utils import GenerationConfig
tokenizer = AutoTokenizer.from_pretrained("trillionmonster/Baichuan-13B-Chat-8bit", use_fast=False, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("trillionmonster/Baichuan-13B-Chat-8bit", device_map="auto", trust_remote_code=True)
model.generation_config = GenerationConfig.from_pretrained("trillionmonster/Baichuan-13B-Chat-8bit")
messages = []
messages.append({"role": "user", "content": "世界上第二高的山峰是哪座"})
response = model.chat(tokenizer, messages)
print(response)
如需使用 int4 量化 (Similarly, to use int4 quantization):
model = AutoModelForCausalLM.from_pretrained("trillionmonster/Baichuan-13B-Chat-8bit", device_map="auto",load_in_4bit=True,trust_remote_code=True)
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