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

model = AutoModelForSequenceClassification.from_pretrained("my-flava-model")
tokenizer = AutoTokenizer.from_pretrained("my-flava-model")

def classify_text(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
    with torch.no_grad():
        outputs = model(**inputs)
    prediction = torch.argmax(outputs.logits, dim=1).item()
    return str(prediction)

iface = gr.Interface(fn=classify_text, inputs="text", outputs="text")
iface.launch()