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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() |