app file added

app.py

@@ -0,0 +1,24 @@
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
+tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
+
+import gradio as gr
+
+def greet(my_text):
+    with torch.no_grad():
+        tokens = tokenizer(my_text, padding=True, truncation=True, return_tensors="pt")
+        outputs = model(**tokens)
+        logits = outputs.logits
+        probabilities = torch.softmax(logits, dim=1)
+        label_ids = torch.argmax(probabilities, dim=1)
+        labels = ['Negative', 'Positive']
+        label = labels[label_ids]
+    return label  
+
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text", title="Sentiment Analysis",description ="Classify a text into either Positive or negative",
+article = "hey my nam is pranjal khadka")
+
+demo.launch(share = True)