Update README.md

README.md

@@ -10,7 +10,7 @@ In Transformers
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
-from scipy.special import softmax, expit
+from torch.nn.functional import softmax, sigmoid
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -27,9 +27,11 @@ features = tokenizer([[sentence, l] for l in labels], padding=True, truncation=T
 model.eval()
 with torch.no_grad():
     scores = model(**features).logits
-    print(expit(scores)) #Multi-Label Classification
-    print(softmax(scores)) #Single-Label Classification
-    
+    print("Multi-Label:", sigmoid(scores)) #Multi-Label Classification
+    print("Single-Label:", softmax(scores, dim=0)) #Single-Label Classification
+
+#Multi-Label: tensor([[0.0412],[0.2436],[0.0394],[0.0020],[0.0050],[0.1424]])
+#Single-Label: tensor([[0.0742],[0.5561],[0.0709],[0.0035],[0.0087],[0.2867]])
 ```