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import gradio as gr | |
title = "Disaster Tweets Classification" | |
description = "Text classification using DistilBERT fine-tuned on the Kaggle disaster tweets dataset. \n\nLabels:\n- LABEL_1 - About disaster \n- LABEL_0 - Not about disaster" | |
examples = [["Twelve feared killed in an air ambulance helicopter crash"], | |
["Just happened a terrible car crash"], | |
["Heard about #earthquake in different cities"], | |
["I love my new Tesla!"], | |
["Wow social media really blew up after the Adele concert"]] | |
interface = gr.Interface.load("huggingface/hkayesh/twitter-disaster-nlp", | |
title=title, | |
description=description, | |
examples=examples, | |
theme="peach" | |
) | |
interface.launch(enable_queue=True) |