import gradio as gr from datasets import load_dataset, Audio import torch from transformers import pipeline pipeline = pipeline("audio-classification", model="DanielDBGC/my_awesome_lang_class_mind_model") def predict(input_sound): predictions = pipeline(input_sound["path"]) return {p["label"]: p["score"] for p in predictions} gradio_app = gr.Interface( fn = predict, inputs= [gr.Audio(label="Record or upload someone speaking!", sources=['upload', 'microphone'], type="filepath")], outputs= [gr.Label(label="Result", num_top_classes=3)], title="Guess the language!", ) if __name__ == "__main__": gradio_app.launch()