This model is trained from Mistral-7B-Instruct-V0.2 with 90% chinese dataset and 10% english dataset
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from transformers import GenerationConfig, LlamaForCausalLM, LlamaTokenizer,AutoTokenizer,AutoModelForCausalLM,MistralForCausalLM
import torch
model_id=Mistral-7B-Instruct-v0.3
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id,torch_dtype=torch.bfloat16,device_map="auto",)
prompt = "[INST] <<SYS>>\nYou are a helpful, respectful and honest assistant.Help humman as much as you can.\n<</SYS>>\n\n{instruction} [/INST]"
text = prompt.format_map({"instruction":"你好,最近干嘛呢"})
def predict(content_prompt):
inputs = tokenizer(content_prompt,return_tensors="pt",add_special_tokens=True)
input_ids = inputs["input_ids"].to("cuda:0")
# print(f"input length:{len(input_ids[0])}")
with torch.no_grad():
generation_output = model.generate(
input_ids=input_ids,
#generation_config=generation_config,
return_dict_in_generate=True,
output_scores=True,
max_new_tokens=2048,
top_p=0.9,
num_beams=1,
do_sample=True,
repetition_penalty=1.0,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.pad_token_id,
)
s = generation_output.sequences[0]
output = tokenizer.decode(s,skip_special_tokens=True)
output1 = output.split("[/INST]")[-1].strip()
# print(output1)
return output1
predict(text)
output:你好!作为一个大型语言模型,我一直在学习和提高自己的能力。最近,我一直在努力学习新知识、改进算法,以便更好地回答用户的问题并提供帮助。同时,我也会定期接受人工智能专家的指导和评估,以确保我的表现不断提升。希望这些信息对你有所帮助!
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