class_docstr: Example:
  
  ```py
  from transformers.tools import TextClassificationTool
  
  classifier = TextClassificationTool()
  classifier("This is a super nice API!", labels=["positive", "negative"])
  ```
code: def decode(self, outputs):
      logits = outputs.logits
      label_id = torch.argmax(logits[:, 2]).item()
      return self._labels[label_id]
  
imports: import torch
  from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
  from .base import PipelineTool
label_desc: Use image node_id 3 for calling the TextClassificationTool obj's underlying member method code with example usage: obj.decode(outputs) and returns: self