independently of the inputs. The caveats from the previous section still apply.
Pipeline custom code
If you want to override a specific pipeline.
Don't hesitate to create an issue for your task at hand, the goal of the pipeline is to be easy to use and support most
cases, so transformers could maybe support your use case.
If you want to try simply you can:
Subclass your pipeline of choice
```python
class MyPipeline(TextClassificationPipeline):
    def postprocess():
        # Your code goes here
        scores = scores * 100
        # And here
my_pipeline = MyPipeline(model=model, tokenizer=tokenizer, ...)
or if you use pipeline function, then:
my_pipeline = pipeline(model="xxxx", pipeline_class=MyPipeline)
```
That should enable you to do all the custom code you want.
Implementing a pipeline
