import gradio as gr | |
# Assuming this is the correct path to your model and it returns a usable object. | |
model = gr.Interface.load("models/NousResearch/Yarn-Mistral-7b-64k") | |
# Define a function that uses your model for inference, ensuring that the 'model' can predict. | |
def predict(input): | |
# Example prediction code. Replace with actual prediction logic. | |
return model(input) | |
# Create a Gradio interface | |
interface = gr.Interface(fn=predict, inputs="text", outputs="text") | |
# Launch the interface with share=True to create a public link. | |
interface.launch(share=True) | |