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from transformers import AutoTokenizer, AutoModelForTokenClassification | |
from transformers.pipelines import pipeline | |
import gradio as gr | |
from huggingface_hub import login | |
import os | |
login(os.environ['HF_Token']) | |
masker = pipeline( | |
task="token-classification", | |
model="Isotonic/distilbert_finetuned_ai4privacy", | |
device="cpu", | |
) | |
def ai4p_gradio(input): | |
entities = masker(input) | |
return {"text": input, "entities": entities} | |
demo = gr.Interface( | |
fn=ai4p_gradio, | |
inputs=gr.Textbox(lines=5, label="Input"), | |
outputs=gr.HighlightedText(label="output"), | |
) | |
demo.launch() |