metadata
language:
- en
tags:
- text2sql
- causal-lm
- transformers
- safetensors
license: mit
pipeline_tag: text-generation
base_model:
- microsoft/Phi-3-mini-4k-instruct
library_name: transformers
Phi-3 Text-to-SQL Model
This is a fine-tuned Microsoft Phi-3 model specialized for Text-to-SQL generation.
Example
from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "bhavika67/text2sql"
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_pretrained(repo_id, torch_dtype="auto", device_map="auto")
question = "List all customers who ordered products over $500 last month."
inputs = tokenizer(question, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=128)
sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(sql_query)