Delete handler.py

handler.py

@@ -1,31 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-from transformers import DataCollatorWithPadding
-from torch.nn.functional import softmax
-
-import torch
-from typing import Any, Dict, List
-
-
-class EndpointHandler:
-    def __init__(self, path=""):
-        self.tokenizer = AutoTokenizer.from_pretrained(path)
-        self.model = AutoModelForSequenceClassification.from_pretrained(path)
-        self.tokenizer.pad_token = self.tokenizer.eos_token
-        self.model.config.pad_token_id = self.tokenizer.pad_token_id
-
-    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
-        batch_of_strings = data["inputs"]
-
-        tokens = self.tokenizer(
-            batch_of_strings, padding=True, truncation=True, return_tensors="pt"
-        )
-
-        # Calculate the loss
-        with torch.no_grad():
-            outputs = self.model(**tokens)
-
-        probabilities = softmax(outputs.logits, dim=1)
-
-        return {
-            "predictions": [pred[0] for pred in probabilities.tolist()],
-        }