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Updated typo's in multiple documents.md (#7728)
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* Update addons.md

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nallave authored Feb 26, 2025
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2 changes: 1 addition & 1 deletion docs/guide/addons.md
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Expand Up @@ -73,7 +73,7 @@ tfxa.feast_examplegen.FeastExampleGen(...)

Client library to inspect content in [ML Metadata](mlmd.md) populated by TFX pipelines.

[:octicons-arrow-right-24: MLMD Cleint](https://github.com/tensorflow/tfx-addons/tree/main/tfx_addons/mlmd_client)
[:octicons-arrow-right-24: MLMD Client](https://github.com/tensorflow/tfx-addons/tree/main/tfx_addons/mlmd_client)

- [__Model Card Generator__](https://github.com/tensorflow/tfx-addons/tree/main/tfx_addons/model_card_generator)

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4 changes: 2 additions & 2 deletions docs/guide/examplegen.md
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Expand Up @@ -248,7 +248,7 @@ Retrieving a certain span can be done with RangeConfig, which is detailed below.
### Date

!!! Note
This feature is only availible after TFX 0.24.0.
This feature is only available after TFX 0.24.0.

If your data source is organized on filesystem by date, TFX supports mapping
dates directly to span numbers. There are three specs to represent mapping from
Expand Down Expand Up @@ -308,7 +308,7 @@ example_gen = CsvExampleGen(input_base='/tmp', input_config=input)
### Version

!!! Note
This feature is only availible after TFX 0.24.0.
This feature is only available after TFX 0.24.0.

Version can be retrieved by using '{VERSION}' spec in the
[input glob pattern](https://github.com/tensorflow/tfx/blob/master/tfx/proto/example_gen.proto):
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2 changes: 1 addition & 1 deletion docs/guide/index.md
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Expand Up @@ -248,7 +248,7 @@ frameworks, including [Apache Airflow](airflow.md),
portable to different computing platforms, including on-premise, and
cloud platforms such as the
[Google Cloud Platform (GCP)](https://cloud.google.com/). In particular,
TFX interoperates with serveral managed GCP services, such as
TFX interoperates with several managed GCP services, such as
[Cloud AI Platform](https://cloud.google.com/ai-platform/) for
[Training and Prediction](https://cloud.google.com/ml-engine/), and
[Cloud Dataflow](https://cloud.google.com/dataflow/) for distributed data
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