from sentiment_wrapper import PredictionModel import gradio as gr model = PredictionModel() def predict(text:str): result = model.predict([text])[0] return f'class: {result}' markdown_text = '''

This space provides a gradio demo and an easy-to-run wrapper of the pre-trained model for fine-grained sentiment analysis in Norwegian language, pre-trained on the NoReC dataset. Information about project you an fine on the website of [University of Oslo](https://www.mn.uio.no/ifi/english/research/projects/sant/) ## How to do inference? Specify in config.json which model from saved_models you want to use. The model can be easily used for predicting sentiment as follows: ```python >>> from sentiment_wrapper import PredictionModel >>> model = PredictionModel() >>> model.predict(['vi liker svart kaffe', 'jeg elsker virkelig røde roser!']) [5,5] ``` ## How to fine-tune? For this run fine-tune.py and specify required arguments: If you want to use custom wrapper, please specify: -custom_wrapper = True There are also additional arguments possible but not required: ''' with gr.Blocks() as demo: with gr.Row(equal_height=False) as row: text_input = gr.Textbox(label="input") text_output = gr.Textbox(label="output") with gr.Row(scale=4) as row: text_button = gr.Button("submit").style(full_width=True) text_button.click(fn=predict, inputs=text_input, outputs=text_output) gr.Markdown(markdown_text) demo.launch()