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#!python
# -*- coding: utf-8 -*-
# @author: Kun
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
max_token: int = 10000 # 10000 # 64
temperature: float = 0.75
top_p = 0.9
use_lora = False
# def load_model():
# model_name_or_path = "baichuan-inc/baichuan-7B"
# # model_name_or_path = "~/.cache/huggingface/hub/models--baichuan-inc--baichuan-7B/snapshots/39916f64eb892ccdc1982b0eef845b3b8fd43f6b/"
# tokenizer = AutoTokenizer.from_pretrained(
# model_name_or_path,
# trust_remote_code=True)
# model = AutoModelForCausalLM.from_pretrained(
# model_name_or_path,
# device_map="auto",
# trust_remote_code=True)
# # inputs = tokenizer('登鹳雀楼->王之涣\n夜雨寄北->', return_tensors='pt')
# # inputs = inputs.to('cuda:0')
# # pred = model.generate(**inputs, max_new_tokens=64,repetition_penalty=1.1)
# # print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
# return tokenizer, model
def load_model(use_lora=True, LOAD_IN_8BIT=False):
"""
params:
use_lora=True, LOAD_IN_8BIT=False
use_lora=False. LOAD_IN_8BIT=True
"""
tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/baichuan-7B",
trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("baichuan-inc/baichuan-7B",
device_map="auto",
trust_remote_code=True,
load_in_8bit=LOAD_IN_8BIT, # if not have enough GPU memory, then use 8bit
)
if use_lora:
model = PeftModel.from_pretrained(model, "hiyouga/baichuan-7b-sft")
return tokenizer, model
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