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