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| import gradio as gr | |
| from fastai.text.all import load_learner | |
| import os | |
| import pathlib | |
| import torch | |
| ## Workaround for Windows Path - PathPosix issue | |
| # temp = pathlib.PosixPath | |
| # pathlib.PosixPath = pathlib.WindowsPath | |
| def predict(text): | |
| # Directly use the string path | |
| model_path = "models/LikeItOrNot-base-v1.pkl" | |
| learner = load_learner(model_path) | |
| prediction = learner.predict(text) | |
| confidence_score = torch.tensor(prediction[2]).max() | |
| confidence= f"{confidence_score:.2%}" | |
| if str(prediction[0]) == "1": | |
| label = "NEGATIVE" | |
| elif str(prediction[0]) == "2": | |
| label = "POSITIVE" | |
| else: | |
| label = "dunno" | |
| output = f"Prediction: {label} \n Confidence: {confidence}" | |
| print(prediction) | |
| return output, confidence | |
| iface = gr.Interface(fn=predict, inputs="text", outputs=["label", "text"]) | |
| iface.launch() | |