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import gradio as gr
from transformers import pipeline
def classify_sentiment(audio, model):
pipe = pipeline("audio-classification", model=model)
pred = pipe(audio)
return {dic["label"]: dic["score"] for dic in pred}
input_audio = [gr.inputs.Audio(source="microphone", type="filepath", label="Record/ Drop audio"), gr.inputs.Dropdown(["DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"], label="Model Name")]
label = gr.outputs.Label(num_top_classes=5)
gr.Interface(
fn = classify_sentiment,
inputs = input_audio,
outputs = label,
#examples=[["test1.wav", "DrishtiSharma/wav2vec2-base-finetuned-sentiment-mesd-v11"], ["test2.wav", "hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd"]],
theme="grass").launch()
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