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from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
"""
单轮对话，不具有对话历史的记忆功能
"""
def main():
model_name = 'golaxy/gogpt2-7b'
max_new_tokens = 1024
top_p = 0.9
temperature = 0.95
repetition_penalty = 1.0
device = 'cuda'
input_pattern = '<s>{}</s>'
model = AutoModelForCausalLM.from_pretrained(
model_name,
trust_remote_code=True,
low_cpu_mem_usage=True,
torch_dtype=torch.float16,
device_map='auto'
).to(device).eval()
tokenizer = AutoTokenizer.from_pretrained(
model_name,
trust_remote_code=True,
# llama不支持fast
use_fast=False if model.config.model_type == 'llama' else True
)
text = input('User：')
while True:
text = text.strip()
text = input_pattern.format(text)
input_ids = tokenizer(text, return_tensors="pt", add_special_tokens=False).input_ids.to(device)
with torch.no_grad():
outputs = model.generate(
input_ids=input_ids, max_new_tokens=max_new_tokens, do_sample=True,
top_p=top_p, temperature=temperature, repetition_penalty=repetition_penalty,
eos_token_id=tokenizer.eos_token_id
)
outputs = outputs.tolist()[0][len(input_ids[0]):]
response = tokenizer.decode(outputs)
response = response.strip().replace(text, "").replace('</s>', "").replace('<s>', "").strip()
print("Firefly：{}".format(response))
text = input('User：')
if __name__ == '__main__':
main()
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