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Fix broken links
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melissawm committed Oct 30, 2024
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2 changes: 1 addition & 1 deletion docs/getting_started.md
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Expand Up @@ -16,7 +16,7 @@ In addition to the getting started guides, there are always other MaxText capabi
getting_started/First_run.md
getting_started/steps_model.md
getting_started/End-to-end example <https://www.kaggle.com/code/melissawm/maxtext-examples>
End-to-end example <https://www.kaggle.com/code/melissawm/maxtext-examples>
getting_started/Data_Input_Pipeline.md
getting_started/Data_Input_Perf.md
```
8 changes: 4 additions & 4 deletions docs/getting_started/First_run.md
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Expand Up @@ -28,7 +28,7 @@ python3 MaxText/train.py MaxText/configs/base.yml \
dataset_type=synthetic \
steps=10
```
Next, you can try training on a HugginFace dataset, see [Data Input Pipeline](https://github.com/google/maxtext/blob/main/getting_started/Data_Input_Pipeline.md) for data input options.
Next, you can try training on a HugginFace dataset, see [Data Input Pipeline](Data_Input_Pipeline.md) for data input options.

5. If you want to decode, you can decode as follows.
```
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## Multihost development
There are three patterns for running MaxText with more than one host.

1. [GKE, recommended] [Running Maxtext with xpk](../Run_MaxText_via_xpk.md) - Quick Experimentation and Production support
2. [GCE] [Running Maxtext with Multihost Jobs](Run_MaxText_via_multihost_job.md) - Long Running Production Jobs with Queued Resources
3. [GCE] [Running Maxtext with Multihost Runner](Run_MaxText_via_multihost_runner.md) - Fast experiments via multiple ssh connections.
1. [GKE, recommended] [Running Maxtext with xpk](../guides/Run_MaxText_via_xpk.md) - Quick Experimentation and Production support
2. [GCE] [Running Maxtext with Multihost Jobs](https://github.com/AI-Hypercomputer/maxtext/blob/main/getting_started/Run_MaxText_via_multihost_job.md) - Long Running Production Jobs with Queued Resources
3. [GCE] [Running Maxtext with Multihost Runner](https://github.com/AI-Hypercomputer/maxtext/blob/main/getting_started/Run_MaxText_via_multihost_runner.md) - Fast experiments via multiple ssh connections.

## Preflight Optimizations

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