app.py

import gradio as gr

from transformers import AutoModel, pipeline, AutoTokenizer

access_token = "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"

model = AutoModel.from_pretrained("EkhiAzur/RoBERTA_3", token=access_token)

tokenizer = AutoTokenizer.from_pretrained(
  "ixa-ehu/roberta-eus-euscrawl-large-cased",
  use_fast=use_fast_tokenizer,
  add_prefix_space=True,
)

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer, max_length=512,
                padding=True, truncation=True, batch_size=1)

def prozesatu(testua):
    prediction = prozesatu.classifier(testua)
    return f'C1:{prediction["label"]}. Probabilitatea:{prediction["score"]}'

prozesatu.classifier = classifier

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