app.py

import gradio as gr
from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer

# Load model and tokenizer
model_name = "peterkros/immunization-classification-model"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Define the pipeline
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

def classify_text(text):
    # Get predictions
    predictions = classifier(text)
    return predictions

# Create Gradio interface
iface = gr.Interface(
    fn=classify_text,
    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter text here..."),
    outputs=gr.outputs.JSON(),
    title="Text Classification with DistilBERT",
    description="Enter text to classify it using a DistilBERT model trained for text classification."
)

# Launch the app
if __name__ == "__main__":
    iface.launch()