Update app.py

app.py

@@ -1,35 +1,35 @@
-# import gradio as gr
+import gradio as gr
 
-# gr.load("models/AnkitAI/reviews-roberta-base-sentiment-analysis").launch()
+gr.load("models/AnkitAI/reviews-roberta-base-sentiment-analysis").launch()
 
-import gradio as gr
-from transformers import RobertaTokenizer, RobertaForSequenceClassification
-import torch
+# import gradio as gr
+# from transformers import RobertaTokenizer, RobertaForSequenceClassification
+# import torch
 
-# Load the model and tokenizer
-model_name = "AnkitAI/reviews-roberta-base-sentiment-analysis"
-model = RobertaForSequenceClassification.from_pretrained(model_name)
-tokenizer = RobertaTokenizer.from_pretrained(model_name)
+# # Load the model and tokenizer
+# model_name = "AnkitAI/reviews-roberta-base-sentiment-analysis"
+# model = RobertaForSequenceClassification.from_pretrained(model_name)
+# tokenizer = RobertaTokenizer.from_pretrained(model_name)
 
-# Define a function to perform sentiment analysis and map labels
-def predict_sentiment(text):
-    inputs = tokenizer(text, return_tensors="pt")
-    outputs = model(**inputs)
-    logits = outputs.logits
-    predicted_class_id = torch.argmax(logits, dim=1).item()
+# # Define a function to perform sentiment analysis and map labels
+# def predict_sentiment(text):
+#     inputs = tokenizer(text, return_tensors="pt")
+#     outputs = model(**inputs)
+#     logits = outputs.logits
+#     predicted_class_id = torch.argmax(logits, dim=1).item()
     
-    # Map class id to label
-    labels = ["Negative", "Positive"]
-    return labels[predicted_class_id]
+#     # Map class id to label
+#     labels = ["Negative", "Positive"]
+#     return labels[predicted_class_id]
 
-# Create a Gradio interface
-interface = gr.Interface(
-    fn=predict_sentiment,
-    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter a review here..."),
-    outputs="text",
-    title="Reviews Sentiment Analysis",
-    description="Enter an Amazon review to see if it is positive or negative."
-)
+# # Create a Gradio interface
+# interface = gr.Interface(
+#     fn=predict_sentiment,
+#     inputs=gr.inputs.Textbox(lines=2, placeholder="Enter a review here..."),
+#     outputs="text",
+#     title="Reviews Sentiment Analysis",
+#     description="Enter an Amazon review to see if it is positive or negative."
+# )
 
-# Launch the interface
-interface.launch()
+# # Launch the interface
+# interface.launch()