first commit

app.py

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+import torch
+import streamlit as st
+import numpy as np
+from PIL import Image, ImageDraw
+from transformers import pipeline
+from tempfile import NamedTemporaryFile
+
+audiopipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3")st.title('Upload an audio file for speech recognition')
+
+uploaded_audio_file = st.file_uploader("Choose an audio file (wav)")
+if uploaded_audio_file is not None:
+    with NamedTemporaryFile(suffix="wav") as temp:
+        temp.write(uploaded_audio_file.getvalue())
+        temp.seek(0)
+        result = audiopipe(temp.name)
+        st.write(result)

requirements.txt

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+streamlit
+accelerate
+transformers