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import os
import streamlit as st
from speechbrain.pretrained.interfaces import foreign_class
from faster_whisper import WhisperModel
# -------------------------------
# Load Model (Cached)
# -------------------------------
@st.cache_resource(show_spinner="Loading model...") # making sure we only load the model once per every app instance
def load_accent_model():
"""Loads custom accent classification model."""
if not os.getenv("HF_TOKEN"):
st.error("Hugging Face token not found.")
st.stop()
try:
return foreign_class(
source="Jzuluaga/accent-id-commonaccent_xlsr-en-english",
pymodule_file="custom_interface.py",
classname="CustomEncoderWav2vec2Classifier"
)
except Exception as e:
st.error(f"❌ Error loading model: {e}")
st.stop()
@st.cache_resource(show_spinner="Loading Whisper...")
def load_whisper():
return WhisperModel("tiny", device="cpu", compute_type="int8_float32")
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