Remove need for label binarizer

handler.py

@@ -1,6 +1,5 @@
 from typing import  Dict, List, Any
 from transformers import AutoModel, AutoTokenizer
-import pickle
 
 
 class EndpointHandler():
@@ -22,8 +21,7 @@ class EndpointHandler():
         inputs = self.tokenizer(text, padding="max_length")
         preds = self.model(input_ids=[inputs["input_ids"]])
 
-        with open("label_binarizer.pkl", "rb") as f:
-            label_binarizer = pickle.loads(f.read())
+        id2label = self.model.config.id2label
 
-        prediction = [[{label: p} for label, p in zip(label_binarizer.classes_, preds[0].tolist()) if p > 0.5]]
+        prediction = [[{id2label[label_id]: p} for label_id, p in enumerate(preds[0].tolist()) if p > 0.5]]
         return prediction

requirements.txt

@@ -1,4 +0,0 @@
-optimum[onnxruntime]==1.2.3
-scikit-learn==1.2.2
-mkl-include
-mkl