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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):
print(input_sound)
predictions = pipeline(input_sound)
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() |