Update app.py

app.py

@@ -2,14 +2,15 @@ import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-# Initialize device
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# Initialize device - force CPU usage
+device = "cpu"
 print(f"Using device: {device}")
 
 # Load model and tokenizer
 model_name = "tabularisai/robust-sentiment-analysis"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name).to(device)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)  # Remove .to(device)
+model.eval()  # Set model to evaluation mode
 
 # Define sentiment mapping
 SENTIMENT_MAP = {
@@ -29,12 +30,12 @@ def analyze_sentiment(text, show_probabilities=False):
         text = text.lower()
         
         # Tokenize and prepare input
-        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512).to(device)
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
 
         with torch.no_grad():
             outputs = model(**inputs)
 
-        probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1).cpu().numpy()[0]
+        probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1).numpy()[0]
         predicted_class = probabilities.argmax()
         predicted_sentiment = SENTIMENT_MAP[predicted_class]
         confidence = probabilities[predicted_class]
@@ -61,20 +62,8 @@ def analyze_sentiment(text, show_probabilities=False):
     except Exception as e:
         return f"An error occurred during sentiment analysis: {str(e)}"
 
-# Custom theme
-custom_theme = gr.themes.Soft().set(
-    body_background_fill="*radial-gradient(circle at top left, #f3e7e9, #e3eeff)",
-    block_background_fill="rgba(255, 255, 255, 0.95)",
-    block_border_width="0px",
-    block_shadow="*0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1)",
-    button_primary_background_fill="*linear-gradient(90deg, #4F46E5, #7C3AED)",
-    button_primary_background_fill_hover="*linear-gradient(90deg, #4338CA, #6D28D9)",
-    button_primary_text_color="white",
-    input_background_fill="white",
-)
-
-# Create Gradio interface using Blocks for better layout control
-with gr.Blocks(theme=custom_theme) as demo:
+# Create Gradio interface using Blocks
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown(
         """
         # 🎭 Sentiment Analysis Wizard
@@ -123,6 +112,13 @@ with gr.Blocks(theme=custom_theme) as demo:
         outputs=output
     )
 
+    gr.Markdown(
+        """
+        <div style='text-align: center; padding: 1rem; margin-top: 2rem; font-size: 0.9em; color: #666;'>
+            Developed with ❤️ using Gradio and Transformers by Hugging Face
+        </div>
+        """
+    )
 
 # Launch the interface
 demo.launch()