Update app.py

app.py

@@ -1,25 +1,3 @@
 import gradio as gr
-from transformers import TextClassificationPipeline, AutoTokenizer, AutoModelForSequenceClassification
 
-# Load a pre-trained text classification model 
-model_name = "KoalaAI/Text-Moderation" 
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-
-# Create a TextClassificationPipeline
-pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)
-
-# Define the classify_text function using the pipeline
-def classify_text(text):
-    prediction = pipe(text)[0]
-    return prediction
-
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=classify_text,
-    inputs=gr.components.Textbox(label="Enter text"),
-    outputs=gr.outputs.Label(num_top_classes=None),  # Show all labels
-)
-
-# Launch the Gradio app
-iface.launch()
+gr.Interface.load("models/KoalaAI/Text-Moderation").launch()