download model

app.py

@@ -1,3 +1,19 @@
-from transformers import pipeline
+import streamlit as st
+from huggingface_hub import hf_hub_url, cached_download
+import numpy as np
+from audio_recorder_streamlit import audio_recorder
+from model import RNN
+
+REPO_ID = "BrendaTellez/sounds2"
+FILENAME = "RNN60-GRU.h5"
+RATE = 22050
+
+@st.cache(allow_output_mutation=True)
+def download_model():
+    model = tf.keras.models.load_model(
+        cached_download(hf_hub_url(REPO_ID, FILENAME)))
+    return model
+
+model = download_model()
+st.write(model.summary)
 
-pipe=pipeline("audio-classification", model=BrendaTellez/sounds2)