Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "srujanamadiraju/merged-nl-sql-gemma2b"  # your uploaded model
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
+
+def generate_sql(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    output = model.generate(**inputs, max_new_tokens=128, temperature=0.2, do_sample=True)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+interface = gr.Interface(fn=generate_sql, inputs="text", outputs="text", 
+                         title="Gemma NL2SQL API", 
+                         description="Convert natural language to SQL with merged Gemma model")
+
+interface.launch()