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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() | |