Created app.py

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import BertTokenizer, BertForSequenceClassification
+import torch
+
+# Load the model and tokenizer
+tokenizer = BertTokenizer.from_pretrained("Minej/bert-base-personality")
+model = BertForSequenceClassification.from_pretrained("Minej/bert-base-personality")
+
+# Define the personality detection function
+def personality_detection(text):
+    inputs = tokenizer(text, truncation=True, padding=True, return_tensors="pt")
+    outputs = model(**inputs)
+    predictions = outputs.logits.squeeze().detach().numpy()
+
+    label_names = ['Extroversion', 'Neuroticism', 'Agreeableness', 'Conscientiousness', 'Openness']
+    result = {label_names[i]: predictions[i] for i in range(len(label_names))}
+    return result
+
+# Set up Gradio Interface
+interface = gr.Interface(
+    fn=personality_detection,
+    inputs=gr.Textbox(lines=5, placeholder="Enter text for personality detection..."),
+    outputs=gr.Label(num_top_classes=5),
+    title="Personality Detection from Text",
+    description="This app detects personality traits based on the input text using a fine-tuned BERT model."
+)
+
+# Launch the app
+interface.launch()