Spaces:
Sleeping
Sleeping
import gradio as gr | |
import os | |
path_to_L_model = str(os.environ['path_to_L_model']) | |
path_to_S_model = str(os.environ['path_to_S_model']) | |
read_token = str(os.environ['read_token']) | |
title = "DSA II" | |
description_main = """ | |
A set of models to perform sentiment analysis. Choose between Large-Multilingual or Small-En-only. | |
Select one of the two pages to start querying one of the two models. | |
""" | |
description_L = """ | |
XLM-R tuned model, EN-tuned, pre-trained with 94 languages available (see original model [card](https://huggingface.co/xlm-roberta-large) to see which are available) | |
""" | |
description_S = """ | |
A tuned BERT-base-cased model. | |
""" | |
examples = [ | |
["I was followed by the blue monster but was not scared. I was calm and relaxed."], | |
["Ero seguito dal mostro blu, ma non ero spaventato. Ero calmo e rilassato."], | |
["Śledził mnie niebieski potwór, ale się nie bałem. Byłem spokojny i zrelaksowany."], | |
] | |
interface_words = gr.Interface( | |
fn=None, | |
inputs=None, | |
outputs=None, | |
description=description_main, | |
) | |
interface_model_L = gr.Interface.load( | |
name=path_to_L_model, | |
description=description_L, | |
examples=examples, | |
title=title, | |
api_key=read_token, | |
) | |
interface_model_S = gr.Interface.load( | |
name=path_to_S_model, | |
description=description_S, | |
examples=examples[0], | |
title=title, | |
api_key=read_token, | |
) | |
gr.TabbedInterface( | |
[interface_words, interface_model_L, interface_model_S], | |
["Intro", "Large Multilingual", "Base En"] | |
).launch() |