updated sentiment classifier

sentiment.py

@@ -0,0 +1,21 @@
+import torch
+from transformers import AutoModelForSequenceClassification,AutoTokenizer
+
+model=AutoModelForSequenceClassification.from_pretrained('sentiment_classifier/')
+tokenizer=AutoTokenizer.from_pretrained('sentiment_classifier/')
+
+def classify_sentiment(texts,model=model,tokenizer=tokenizer):
+    """
+        user will pass texts separated by comma
+    """
+    try:
+        texts=texts.split(',')
+    except:
+        pass
+
+    input = tokenizer(texts, padding=True, truncation=True,
+                      return_tensors="pt")
+    logits = model(**input)['logits'].softmax(dim=1)
+    logits = torch.argmax(logits, dim=1)
+    output = ['Positive' if i == 1 else 'Negative' for i in logits]
+    return output