commit from

app.py

@@ -1,6 +1,5 @@
 import streamlit as st
 import numpy as np
-import torch
 
 my_model_name = "istassiy/ysda_2022_ml2_hw3_distilbert_base_uncased"
 
@@ -45,8 +44,11 @@ def load_model():
   model = AutoModel.from_pretrained(my_model_name)
   return tokenizer, model
 
+def sigmoid(x):
+  return 1/(1 + np.exp(-x))
+
 def get_top_predictions(predictions):
-  probs = (torch.sigmoid(predictions) > 0).int().numpy()
+  probs = (sigmoid(predictions) > 0).astype(int)
   probs = probs / np.sum(probs)
 
   res = {}