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Zero
Running
on
Zero
File size: 773 Bytes
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import gradio as gr
from transformers import pipeline
# Load the pipeline (token classification)
token_classifier = pipeline("token-classification", model="WesScivetti/SNACS_English", aggregation_strategy="simple")
def classify_tokens(text):
results = token_classifier(text)
output = ""
for entity in results:
output += f"{entity['word']} ({entity['entity_group']}, score={entity['score']:.2f})\n"
return output.strip()
# Gradio Interface
iface = gr.Interface(
fn=classify_tokens,
inputs=gr.Textbox(lines=4, placeholder="Enter a sentence..."),
outputs="text",
title="Token Classification with Transformers",
description="Named Entity Recognition (NER) using Hugging Face Transformers"
)
iface.launch()
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