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import gradio as gr | |
from transformers import pipeline | |
# Load Whisper model from Hugging Face | |
# This uses the `transformers` library's pipeline to load the model | |
transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3") | |
def transcribe(audio): | |
# Transcribe the audio using the Whisper model | |
result = transcriber(audio)["text"] | |
return result | |
# Create a Gradio Interface | |
interface = gr.Interface( | |
fn=transcribe, | |
inputs=gr.Audio(sources="upload", type="filepath"), | |
outputs="text", | |
title="Whisper Speech-to-Text API", | |
description="Upload an audio file and get a transcription using OpenAI's Whisper model from Hugging Face." | |
) | |
# Launch the interface as an API | |
interface.launch() |