未正确输出SQL

[ZhengyiWang]

运行样例后，大语言模型直接输出4

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
model_path = "Chat2DB/Chat2DB-SQL-7B" # This can be replaced with your local model path
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto", trust_remote_code=True, torch_dtype=torch.float16, use_cache=True)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, return_full_text=False, max_new_tokens=100)
prompt = "### Database Schema\n\n['CREATE TABLE \"stadium\" (\\n\"Stadium_ID\" int,\\n\"Location\" text,\\n\"Name\" text,\\n\"Capacity\" int,\\n\"Highest\" int,\\n\"Lowest\" int,\\n\"Average\" int,\\nPRIMARY KEY (\"Stadium_ID\")\\n);', 'CREATE TABLE \"singer\" (\\n\"Singer_ID\" int,\\n\"Name\" text,\\n\"Country\" text,\\n\"Song_Name\" text,\\n\"Song_release_year\" text,\\n\"Age\" int,\\n\"Is_male\" bool,\\nPRIMARY KEY (\"Singer_ID\")\\n);', 'CREATE TABLE \"concert\" (\\n\"concert_ID\" int,\\n\"concert_Name\" text,\\n\"Theme\" text,\\n\"Stadium_ID\" text,\\n\"Year\" text,\\nPRIMARY KEY (\"concert_ID\"),\\nFOREIGN KEY (\"Stadium_ID\") REFERENCES \"stadium\"(\"Stadium_ID\")\\n);', 'CREATE TABLE \"singer_in_concert\" (\\n\"concert_ID\" int,\\n\"Singer_ID\" text,\\nPRIMARY KEY (\"concert_ID\",\"Singer_ID\"),\\nFOREIGN KEY (

\"concert_ID\") REFERENCES \"concert\"(\"concert_ID\"),\\nFOREIGN KEY (\"Singer_ID\") REFERENCES \"singer\"(\"Singer_ID\")\\n);']\n\n\n### Task \n\nBased on the provided database schema information, How many singers do we have?[SQL]\n"
response = pipe(prompt)[0]["generated_text"]
print(response)

尝试其他prompt例子，大语言模型也未像chat2db ai一样直接输出sql

[lordk911]

同样的问题：

>>> print(response)


### Answer 
255

[baisui1981]

这个模型的出处是哪儿？

[loli0123456789]

官方怎么说？