| from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| self.model = AutoModelForSequenceClassification.from_pretrained( | |
| path, | |
| ignore_mismatched_sizes=True # ضروري لتجاوز المشكلة | |
| ) | |
| self.tokenizer = AutoTokenizer.from_pretrained(path) | |
| self.pipeline = pipeline("text-classification", model=self.model, tokenizer=self.tokenizer) | |
| def __call__(self, data): | |
| inputs = data.get("inputs") if isinstance(data, dict) else data | |
| return self.pipeline(inputs) | |