| import sklearn |
| import gradio as gr |
| import joblib |
|
|
| pipe = joblib.load("./pipeline.pkl") |
| inputs = [gr.Textbox(value = "I love this!")] |
| outputs = [gr.Label(label = "Sentiment")] |
| title = "Sentiment Analysis Classifier" |
| description = "This is a sentiment classifier using longformer model with a logistic regression head. " |
| def infer(inputs): |
| predictions = pipe.predict_proba([inputs]) |
| label = { |
| "negative":str(predictions[0][0]), |
| "positive":str(predictions[0][1]), |
| } |
| return label |
| gr.Interface(infer, inputs = inputs, outputs = outputs, title = title, description = description).launch() |
