File size: 1,099 Bytes
a479e48 3dbaaa3 a479e48 7adfed6 3dbaaa3 92d606f 3dbaaa3 3dede03 3dbaaa3 3dede03 a479e48 7adfed6 3dede03 7adfed6 a479e48 7adfed6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 |
import gradio as gr
from fake_job_detector.models import DistilBERTBaseModel
def process_input(title, description):
# Load the safetensors
safetensors_path = "synthetic_data_5epoch"
# Load the DistilBERT model
model = DistilBERTBaseModel(safetensors_path)
result = model(title, description)
verdict = ""
if (result):
verdict = "This job advertisement is likely fraudulent!"
else:
verdict = "This job advertisement is unlikely to be fraudulent."
return verdict
def main():
# Define the interface
interface = gr.Interface(
fn=process_input, # the function to process input
inputs=[gr.Textbox(label="Title"), gr.Textbox(label="Description", lines=4)], # input fields
outputs=gr.Textbox(label="Output"), # output field
title="Fraudulent Job Advertisement Detection",
description="This model aims to detect fraudulent job advertisements given their title and desscription for COMP6713: NLP project"
)
# Launch the interface
interface.launch()
if __name__ == "__main__":
main()
|