Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+model_id = "Mayur74/Llama-2-7b-chat-finetune"  # your uploaded model
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
+
+# Set up pipeline
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Define generation function
+def generate_prompt(prompt):
+    output = pipe(prompt, max_new_tokens=300, temperature=0.7)
+    return output[0]["generated_text"]
+
+# Create Gradio Interface
+demo = gr.Interface(
+    fn=generate_prompt,
+    inputs=gr.Textbox(lines=5, label="Base Prompt"),
+    outputs="text",
+    title="🧠 LLaMA 2 Prompt Optimizer",
+    description="Enter your prompt and get an optimized version.",
+)
+
+# Enable API mode
+demo.launch(share=False, server_name="0.0.0.0", server_port=7860)