glms.py

import os
# os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3,4,5,6,7"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"


import torch
import numpy as np

from transformers import AutoModelForSequenceClassification, AutoModelForMultipleChoice, AutoModel
from transformers import TrainingArguments, Trainer
from transformers import AutoTokenizer
from transformers import DataCollatorWithPadding
from datasets import load_dataset
from datasets import load_metric
import torchsnooper

model_name = "THUDM/chatglm-6b"

if __name__ == "__main__":
    device = "cuda" if torch.cuda.is_available() else "cpu"
    tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)    
    model = AutoModel.from_pretrained(model_name, trust_remote_code=True).half().cuda()
    response, history = model.chat(tokenizer, "你好", history=[])
    print(response)
    response, history = model.chat(tokenizer, "晚上睡不着应该怎么办", history=history)
    print(response)