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[docs] Follow up register_pipeline (#35310)

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18
docs/source/en/add_new_pipeline.md
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@ -184,7 +184,7 @@ class PairClassificationPipeline(Pipeline):
```
The implementation is framework agnostic, and will work for PyTorch and TensorFlow models. If we have saved this in
a file named `pair_classification.py`, we can then import it and register it like this. The [register_pipeline](https://github.com/huggingface/transformers/blob/9feae5fb0164e89d4998e5776897c16f7330d3df/src/transformers/pipelines/base.py#L1387) function registers the pipeline details (task type, pipeline class, supported backends) to a models `config.json` file.
a file named `pair_classification.py`, we can then import it and register it like this.
```py
from pair_classification import PairClassificationPipeline
@ -199,6 +199,22 @@ PIPELINE_REGISTRY.register_pipeline(
)
```
The [register_pipeline](https://github.com/huggingface/transformers/blob/9feae5fb0164e89d4998e5776897c16f7330d3df/src/transformers/pipelines/base.py#L1387) function registers the pipeline details (task type, pipeline class, supported backends) to a models `config.json` file.
```json
"custom_pipelines": {
"pair-classification": {
"impl": "pair_classification.PairClassificationPipeline",
"pt": [
"AutoModelForSequenceClassification"
],
"tf": [
"TFAutoModelForSequenceClassification"
],
}
},
```
Once this is done, we can use it with a pretrained model. For instance `sgugger/finetuned-bert-mrpc` has been
fine-tuned on the MRPC dataset, which classifies pairs of sentences as paraphrases or not.