Delete custom_pipeline.py

custom_pipeline.py

@@ -1,32 +0,0 @@
-'''
- # @ Author: ASJC Team
- # @ Create Time: 2025-11-25 23:52:55
- # @ Modified by: ASJC Team
- # @ Modified time: 2025-11-25 23:53:08
- # @ Description: Custom pipeline for multi-label classification with fine-tuned SciBERT model.
- '''
-
-from transformers import TextClassificationPipeline
-import torch
-
-class ASJCMultiLabelPipeline(TextClassificationPipeline):
-    def __init__(self, *args, **kwargs):
-        self.threshold = kwargs.pop("threshold", None)
-        super().__init__(*args, **kwargs)
-
-        # If no explicit threshold passed → use threshold from config.json
-        if self.threshold is None:
-            self.threshold = getattr(self.model.config, "threshold", 0.3)
-
-    def postprocess(self, model_outputs, **kwargs):
-        scores = torch.sigmoid(torch.tensor(model_outputs["logits"])).tolist()
-        results = []
-
-        for i, score in enumerate(scores):
-            if score >= self.threshold:
-                label = self.model.config.id2label[str(i)]
-                results.append({"label": label, "score": float(score)})
-
-        # Sort by score descending
-        results = sorted(results, key=lambda x: x["score"], reverse=True)
-        return results