Update app.py

app.py

@@ -3,8 +3,20 @@ import streamlit
 
 from transformers.pipelines import pipeline
 
-pipe = pipeline(model="KELONMYOSA/wav2vec2-xls-r-300m-emotion-ru", trust_remote_code=True)
 
-# The pipeline input can be a file, path or link
-result = pipe("DC_a01.wav")
-streamlit.write(result)
+# Use a pipeline as a high-level helper
+
+
+pipe = pipeline("zero-shot-classification", model="knowledgator/comprehend_it-base")
+
+candidate_labels = ['travel', 'cooking', 'dancing', 'exploration']
+st.write(classifier(sequence_to_classify, candidate_labels, multi_label=True))
+#{'labels': ['travel', 'exploration', 'dancing', 'cooking'],
+# 'scores': [0.9945111274719238,
+#  0.9383890628814697,
+#  0.0057061901316046715,
+#  0.0018193122232332826],
+# 'sequence': 'one day I will see the world'}
+
+
+