| import gradio as gr |
| import skops.io as sio |
|
|
| pipe = sio.load("./Model/drug_pipeline.skops", trusted=True) |
|
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|
|
| def predict_drug(): |
| predicted_drug = pipe.score() |
|
|
| |
| return predicted_drug |
|
|
|
|
| outputs = [gr.Label(num_top_classes=5)] |
|
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|
|
|
| title = "Drug Classification" |
| description = "Enter the details to correctly identify Drug type?" |
| article = "This app is a part of the Beginner's Guide to CI/CD for Machine Learning. It teaches how to automate training, evaluation, and deployment of models to Hugging Face using GitHub Actions." |
|
|
|
|
| gr.Interface( |
| fn=predict_drug, |
| outputs=outputs, |
| title=title, |
| description=description, |
| article=article, |
| theme=gr.themes.Soft(), |
| ).launch() |
|
|