Delete pipeline.py

pipeline.py

@@ -1,30 +0,0 @@
-from transformers import PIPELINE_REGISTRY, TokenClassificationPipeline
-import torch
-
-@PIPELINE_REGISTRY.register_pipeline(task="multi_label_token_classification", pipeline_class=None)
-class MultiLabelTokenClassificationPipeline(TokenClassificationPipeline):
-    def __init__(self, model, tokenizer, **kwargs):
-        super().__init__(model=model, tokenizer=tokenizer, **kwargs)
-        self.id2label = {
-            0: 'O',
-            1: 'B-STEREO',
-            2: 'I-STEREO',
-            3: 'B-GEN',
-            4: 'I-GEN',
-            5: 'B-UNFAIR',
-            6: 'I-UNFAIR'
-        }
-
-    def postprocess(self, model_outputs, **kwargs):
-        results = []
-        for logits, tokens in zip(model_outputs[0], model_outputs[1]):
-            probabilities = torch.sigmoid(logits)
-            predicted_labels = (probabilities > 0.5).int()
-            token_results = []
-            for i, token in enumerate(tokens):
-                if token not in self.tokenizer.all_special_tokens:
-                    label_indices = (predicted_labels[i] == 1).nonzero(as_tuple=False).squeeze(-1)
-                    labels = [self.id2label[idx.item()] for idx in label_indices] if label_indices.numel() > 0 else ['O']
-                    token_results.append({"token": token, "labels": labels})
-            results.append(token_results)
-        return results