app.py

# Imports
import os
import torch
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
import transformers
import gradio as gr

model_name = "MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7"
tokenizer = AutoTokenizer.from_pretrained(model_name)

def clasificador(input1, input2):
    classifier = pipeline("zero-shot-classification", model="MoritzLaurer/mDeBERTa-v3-base-mnli-xnli",tokenizer=tokenizer)
    sequence_to_classify = input1
    input2_list = input2.split(",") # Parse the input string as a list 
    candidate_labels= [item.strip() for item in input2_list]
    output = classifier(sequence_to_classify, candidate_labels, multi_label=False)
    return output


iface = gr.Interface(
    fn=clasificador,
    inputs=[gr.inputs.Textbox(label="Ingrese texto"),gr.inputs.Textbox(label="Ingrese lista de labels")],
    outputs=gr.outputs.Textbox(label="Clasificación")
)

iface.launch()