Update app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load your fine-tuned model
+model_name = "ayeshaNoor1/Llama_finetunedModel-1b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the text generation function
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs.input_ids, max_length=100, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=generate_text,
+    inputs="text",
+    outputs="text",
+    title="Fine-Tuned Llama 3.2 Generator",
+    description="Enter a prompt to generate text using the fine-tuned Llama model.",
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    interface.launch()