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Update add_new_pipeline.md (#26197)

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fixed a few typos
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Nino Risteski
2023-09-19 00:41:16 +02:00
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parent 7d4e0c23c8
commit 500dfb5b03
1 changed files with 6 additions and 6 deletions
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docs/source/en/add_new_pipeline.md
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@@ -111,8 +111,8 @@ def _sanitize_parameters(self, **kwargs):
``` ```
Try to keep the inputs/outputs very simple and ideally JSON-serializable as it makes the pipeline usage very easy Try to keep the inputs/outputs very simple and ideally JSON-serializable as it makes the pipeline usage very easy
without requiring users to understand new kind of objects. It's also relatively common to support many different types without requiring users to understand new kinds of objects. It's also relatively common to support many different types
of arguments for ease of use (audio files, can be filenames, URLs or pure bytes) of arguments for ease of use (audio files, which can be filenames, URLs or pure bytes)
@@ -219,8 +219,8 @@ repo.push_to_hub()
``` ```
This will copy the file where you defined `PairClassificationPipeline` inside the folder `"test-dynamic-pipeline"`, This will copy the file where you defined `PairClassificationPipeline` inside the folder `"test-dynamic-pipeline"`,
along with saving the model and tokenizer of the pipeline, before pushing everything in the repository along with saving the model and tokenizer of the pipeline, before pushing everything into the repository
`{your_username}/test-dynamic-pipeline`. After that anyone can use it as long as they provide the option `{your_username}/test-dynamic-pipeline`. After that, anyone can use it as long as they provide the option
`trust_remote_code=True`: `trust_remote_code=True`:
```py ```py
@@ -232,9 +232,9 @@ classifier = pipeline(model="{your_username}/test-dynamic-pipeline", trust_remot
## Add the pipeline to 🤗 Transformers ## Add the pipeline to 🤗 Transformers
If you want to contribute your pipeline to 🤗 Transformers, you will need to add a new module in the `pipelines` submodule If you want to contribute your pipeline to 🤗 Transformers, you will need to add a new module in the `pipelines` submodule
with the code of your pipeline, then add it in the list of tasks defined in `pipelines/__init__.py`. with the code of your pipeline, then add it to the list of tasks defined in `pipelines/__init__.py`.
Then you will need to add tests. Create a new file `tests/test_pipelines_MY_PIPELINE.py` with example with the other tests. Then you will need to add tests. Create a new file `tests/test_pipelines_MY_PIPELINE.py` with examples of the other tests.
The `run_pipeline_test` function will be very generic and run on small random models on every possible The `run_pipeline_test` function will be very generic and run on small random models on every possible
architecture as defined by `model_mapping` and `tf_model_mapping`. architecture as defined by `model_mapping` and `tf_model_mapping`.