import json | |
from typing import Any, Dict, List | |
import sklearn | |
import os | |
import joblib | |
import numpy as np | |
import whatlies | |
class PreTrainedPipeline(): | |
def __init__(self, path: str): | |
# load the model | |
self.model = joblib.load(os.path.join(path, "pipeline.pkl")) | |
def __call__(self, inputs: str): | |
predictions = self.model.predict_proba([inputs]) | |
labels = [] | |
for cls in predictions[0]: | |
labels.append({ | |
"label": f"LABEL_{cls}", | |
"score": predictions[0][cls], | |
}) | |
return labels |