app.py

import gradio as gr
import torch
from transformers import pipeline

app_title = "Portuguese Hate Speech Detection"

app_description = """
This app detects hate speech on Portuguese text using multiple models. You can either introduce your own sentences by filling in "Text" or click on one of the examples provided below.
"""

model_list = [
    "knowhate/HateBERTimbau",
    "knowhate/HateBERTimbau-youtube",
    "knowhate/HateBERTimbau-twitter",
    "knowhate/HateBERTimbau-yt-tt",
]

#pipe = pipeline("text-classification", model="knowhate/HateBERTimbau")
#demo = gr.Interface.from_pipeline(pipe)
#demo.launch()

def predict(chosen_model):

    # Initialize the pipeline with the chosen model
    model_pipeline = pipeline("text-classification", model=chosen_model)
    for prediction in model_pipeline:
        label = model_pipeline['label']
    return label

inputs = [
    gr.Textbox(label="Text", value= "As pessoas tem que perceber que ser 'panasca' não é deixar de ser homem, é deixar de ser humano kkk"),
    gr.Dropdown(label="Model", choices=model_list, value=model_list[1])
]

outputs = [
 gr.Label(label="Result"),
]


gr.Interface(fn=predict, inputs=inputs, outputs=outputs, title=app_title, 
             description=app_description).launch()