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from model import DepressionClassifier | |
import gradio as gr | |
import numpy as np | |
#from PIL import Image | |
#import requests | |
import hopsworks | |
import joblib | |
project = hopsworks.login(project='liangc40') | |
#fs = project.get_feature_store() | |
mr = project.get_model_registry() | |
model = mr.get_model("sentimental_analysis_model", version=1) | |
model_dir = model.download() | |
model = torch.load(model_dir + "/sentimental_analysis_model.pkl", map_location=torch.device('cpu')) | |
def analyse(text): | |
label = model(text) | |
return label | |
with gr.Blocks() as demo: | |
gr.Markdown("<h1><center>Sentiment Analysis with Fine-tuned BERT Model") | |
inputs_text=gr.Textbox(placeholder='Type your text for which you want know the sentiment', label='Text') | |
text_button = gr.Button('Analyse Sentiment') | |
output_text_sentiment = gr.Textbox(placeholder='Sentiment of the text.', label='Sentiment') | |
text_button.click(analyse, inputs = inputs_text, outputs = output_text_sentiment) | |
if __name__ == "__main__": | |
demo.launch() |