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import gradio as gr | |
import os | |
# Retrieve token securely from the environment | |
hf_token = os.environ.get("HF_TOKEN") | |
def preprocess_input(input_data): | |
# Implement robust preprocessing logic here | |
# Handle potential `None` values and ensure valid output | |
# Refer to model documentation for specific requirements | |
return preprocessed_data | |
# Load model with optional token | |
iface = gr.Blocks( | |
preprocess_input, # Use the improved preprocess function | |
gr.load("models/pyannote/speaker-diarization-3.1", hf_token=hf_token), | |
) | |
# Launch interface | |
iface.launch(share=True) # Set share=True for a public link | |