Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+
+# Replace with the actual LLaMa3 model ID from Hugging Face Hub when available
+model_id = "varox34/Llama-3-Mistral-v0.2-Instruct-slerp"
+
+def inference(prompt):
+    # Import necessary libraries (replace with LLaMa3-specific ones)
+    from transformers import pipeline
+
+    # Create a pipeline using the LLaMa3 model ID (assuming compatibility)
+    pipe = pipeline("text-generation", model=model_id)
+
+    # Generate text based on the prompt
+    response = pipe(prompt, max_length=250, num_return_sequences=1)[0]["generated_text"]
+    return response
+
+interface = gr.Interface(
+    fn=inference,
+    inputs="text",
+    outputs="text",
+    title="LLama3 Inference",
+    description="Enter a prompt and get text generated by LLaMa3 (if available).",
+)
+
+interface.launch()