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| import os | |
| PATH = '/data/' # at least 150GB storage needs to be attached | |
| os.environ['TRANSFORMERS_CACHE'] = PATH | |
| os.environ['HF_HOME'] = PATH | |
| os.environ['HF_DATASETS_CACHE'] = PATH | |
| os.environ['TORCH_HOME'] = PATH | |
| import gradio as gr | |
| from interfaces.cap import demo as cap_demo | |
| from interfaces.manifesto import demo as manifesto_demo | |
| from interfaces.sentiment import demo as sentiment_demo | |
| from interfaces.emotion import demo as emotion_demo | |
| from interfaces.ner import demo as ner_demo | |
| from interfaces.ner import download_models as download_spacy_models | |
| from utils import download_hf_models | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| f""" | |
| <style> | |
| @import 'https://fonts.googleapis.com/css?family=Source+Sans+Pro:300,400'; | |
| </style> | |
| <div style="display: block; text-align: left; padding:0; margin:0;font-family: "Source Sans Pro", Helvetica, sans-serif;"> | |
| <h1 style="text-align: center;font-size: 17pt;">Babel Machine Demo</h1> | |
| <p style="font-size: 14pt;">This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, emotion coding and Named Entity Recognition systems.<br> | |
| For the coding of complete datasets, please visit the official <a href="https://babel.poltextlab.com/">Babel Machine</a> site.<br> | |
| Please note that named entity inputs are case sensitive.<br> | |
| </p> | |
| </div> | |
| """) | |
| gr.TabbedInterface( | |
| interface_list=[cap_demo, manifesto_demo, sentiment_demo, emotion_demo, ner_demo], | |
| tab_names=["CAP", "Manifesto", "Sentiment (3)", "Emotions (8)", "Named Entity Recognition"], | |
| ) | |
| if __name__ == "__main__": | |
| download_hf_models() | |
| download_spacy_models() | |
| demo.launch() | |
| # TODO: add all languages & domains |