Update README.md

README.md

@@ -154,11 +154,93 @@ completed fine-tuning run shows:
 
 ## Imports (PEFT library):
 ```python
+
 from peft import PeftModel
-from transformers import AutoModelForCausalLM
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load base model
+base_model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen2.5-Coder-0.5B-Instruct"
+)
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(
+    base_model,
+    "AaronTekle/SQLQwen"
+)
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained(
+    "Qwen/Qwen2.5-Coder-0.5B-Instruct"
+)
+
+# Database table context
+schema = """
+Database: company_db
+
+Table: employees
+Columns:
+- employee_id (INT, Primary Key)
+- first_name (VARCHAR)
+- last_name (VARCHAR)
+- department_id (INT)
+- salary (DECIMAL)
+- hire_date (DATE)
+
+Table: departments
+Columns:
+- department_id (INT, Primary Key)
+- department_name (VARCHAR)
+- location (VARCHAR)
+
+Table: projects
+Columns:
+- project_id (INT, Primary Key)
+- project_name (VARCHAR)
+- employee_id (INT, Foreign Key -> employees.employee_id)
+- budget (DECIMAL)
+"""
+
+# User question
+question = "Find the names of employees earning more than 50000."
+
+# Build prompt
+prompt = f"""
+You are an expert SQL query generator.
+
+Generate a SQL query based on the database schema and user question.
+
+Database Schema:
+{schema}
+
+Question:
+{question}
+
+Return only the SQL query without explanation.
+"""
+
+# Tokenize
+inputs = tokenizer(prompt, return_tensors="pt")
+
+# Generate SQL
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=200,
+        do_sample=False,
+        pad_token_id=tokenizer.eos_token_id
+    )
+
+# Display result
+generated_text = tokenizer.decode(
+    outputs[0][inputs["input_ids"].shape[1]:],
+    skip_special_tokens=True
+)
+
+print("\nGenerated SQL:")
+print(generated_text)
 
-base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-0.5B-Instruct")
-model = PeftModel.from_pretrained(base_model, "AaronTekle/SQLQwen")
 ```
 
 ## References: