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import gradio as gr | |
title = "Tagalog RoBERTa" | |
description = "<p style='text-align: center'>Tagalog Gradio Demo for RoBERTa. To use it, simply add your text, or click one of the examples to load them.</p>" | |
article = "<p style='text-align: center'>Improving Large-scale Language Models and Resources for Filipino,Jan Christian Blaise Cruz and Charibeth Cheng,arXiv preprint arXiv:2111.06053,2021</p>" | |
examples = [ | |
['Makulay ang <mask> na suot ni Roberta.','roberta-tagalog-base'], | |
['Nakakasilaw ang sikat ng <mask>.', 'roberta-tagalog-large'], | |
['Malakas ang buhos ng <mask>.', 'roberta-tagalog-large' ] | |
] | |
i1 = gr.Interface.load("huggingface/jcblaise/roberta-tagalog-base") | |
i2 = gr.Interface.load("huggingface/jcblaise/roberta-tagalog-large") | |
def inference(inputtext, model): | |
if model == "roberta-tagalog-base": | |
outlabel = i1(inputtext) | |
if model == "roberta-tagalog-large": | |
outlabel = i2(inputtext) | |
return outlabel | |
gr.Interface( | |
inference, | |
[gr.inputs.Textbox(label="Input text",lines=10),gr.inputs.Dropdown(choices=["roberta-tagalog-base","roberta-tagalog-large"], type="value", default="roberta-tagalog-base", label="model")], | |
[gr.outputs.Label(label="Output")], | |
examples=examples, | |
article=article, | |
title=title, | |
description=description).launch(enable_queue=False) |