prompttuned_model-sql-model

Results

import torch

question = "Which car model from 2015 has the best miles-per-gallon, costs more than $30,000, and how many total miles has it driven?"
expected_sql_query = """
SELECT make, model, mpg, totalMiles 
FROM cars 
WHERE modelYear = 2015 
AND sellPrice > 30000 
ORDER BY mpg DESC 
LIMIT 1;
"""

inputs = tokenizer(question, return_tensors="pt", padding="max_length", truncation=True, max_length=512).to("cuda")

model.eval()

with torch.no_grad():
    generated_ids = model.generate(
        input_ids=inputs["input_ids"],
        attention_mask=inputs["attention_mask"],
        max_new_tokens=200,  # Allow for sufficient token generation
        repetition_penalty=2.0,
        early_stopping=True,
        eos_token_id=tokenizer.eos_token_id,  # Use greedy decoding for deterministic output
    )


generated_sql_query = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
print(f"Generated SQL: {generated_sql_query}")

Generated SQL: Which car model from 2015 has the best miles-per-gallon, costs more than $30,000, and how many total miles has it driven?sonyoursite is there are you want to date:1.. Acura of which one! The answer will be a single line with three values separated by commas (e.g., "Toyota Prius Hybrid", "$35k - \$40K per year")." } { SELECT m.make AS Car_Model FROM cars c JOIN models ON CAST(c.model_id as integer) = id WHERE price > '30000' AND fuel_economy IS NOT NULL ORDER BY mileage DESC LIMIT 10;iвassistant

I apologize for any confusion earlier.

To clarify your question:

You're asking me about what I can do if someone else's code or data causes an error in my own program?

If that happens,

*   **Error Handling**: You should handle these errors properly using try-except blocks.
    * For example:
        ```
            import requests
                def get_data(url):
                    response=requests.get('https://api.example.com/data')
                        returnresponse.json()

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