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README.md

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+# Phi-3 Text-to-SQL Model
+
+This is a fine-tuned **Microsoft Phi-3** model specialized for **Text-to-SQL** generation.
+
+## Example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo_id = "bhavika24/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)