Update app.py

app.py

@@ -68,17 +68,18 @@ The model is trained on a particular collection of books digitised by the Britis
 tokenizer = AutoTokenizer.from_pretrained("BritishLibraryLabs/bl-books-genre")
 
 model = AutoModelForSequenceClassification.from_pretrained("BritishLibraryLabs/bl-books-genre")
-classifier = pipeline('text-classification',model=model, tokenizer=tokenizer, return_all_scores=True)
+classifier = pipeline('text-classification',model=model, tokenizer=tokenizer, top_k=10)
 
 
 def predict(text):
     predictions = classifier(text)
-    return {pred['label']: pred['score'] for pred in predictions[0]}
+    return {pred['label']: pred['score'] for pred in predictions}
+
+
 
 gr.Interface(predict,
     inputs=gr.inputs.Textbox(label="Book title"),
-    outputs=gr.outputs.Label(label="Predicted genre"), 
-    interpretation='shap',  num_shap=5, theme="huggingface",
+    outputs='label', 
+    interpretation='shap',  num_shap=10.0, theme="huggingface",
     examples=sample_text,description=description,article=article,
-   ).launch(enable_queue=True, cache_examples=True)
-
+   ).launch(enable_queue=True)