feat: created gradio app with model
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- app.py +36 -0
.gitignore
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.idea
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app.py
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from transformers import HubertForCTC, Wav2Vec2Processor
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import gradio as gr
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import time
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import torch
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import soundfile as sf
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import requests
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API_URL = "https://api-inference.huggingface.co/models/omarxadel/hubert-large-arabic-egyptian"
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token = os.environ['apikey']
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headers = {"Authorization": token}
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def transcribe(audio, state=""):
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time.sleep(2)
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# Load model from HuggingFace Hub
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with open(audio, "rb") as f:
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data = f.read()
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response = requests.post(API_URL, headers=headers, data=data)
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output = response.json()["text"]
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state += output + " "
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return state, state
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gr.Interface(
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fn=transcribe,
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inputs=[
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gr.Audio(source="microphone", type="filepath", streaming=True),
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"state"
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],
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outputs=[
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"textbox",
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"state"
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],
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live=True).launch(share=True)
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