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import gradio as gr | |
from PIL import Image | |
from sentiment_classification import SentimentClassifier | |
model = SentimentClassifier() | |
model.load('szzzzz/sentiment_classifier_sentence_level_bert_16m') | |
def detect(text): | |
return round(model.rank(text),2) | |
with gr.Blocks() as app: | |
gr.Markdown("Sentiment Classification To 5 Stars") | |
with gr.Tab("Sentiment Classifier"): | |
text_input = gr.Textbox() | |
text_output = gr.Slider(minimum=1,maximum=5) | |
text_button = gr.Button("SentimentClassifier") | |
text_button.click(detect, inputs=text_input, outputs=text_output) | |
app.launch(server_name="0.0.0.0") |