kolchfa-aws 826e6771ed
Refactor ML section - local and remote models (#5609)
* Refactor ML section - local and remote models

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Added command to calculate checksum

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add ONNX format to register API

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add sparse encoding predict example

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add API section

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Refactor the API section

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Typo

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Implemented Vale comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add get connector API

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Reword heading

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Addressed tech review comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Apply suggestions from code review

Co-authored-by: Melissa Vagi <vagimeli@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

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Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: Melissa Vagi <vagimeli@amazon.com>
2023-11-17 15:59:27 -05:00

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Markdown

---
layout: default
title: Using ML models within OpenSearch
has_children: true
nav_order: 50
redirect_from:
- /ml-commons-plugin/model-serving-framework/
---
# Using ML models within OpenSearch
**Generally available 2.9**
{: .label .label-purple }
To integrate machine learning (ML) models into your OpenSearch cluster, you can upload and serve them locally. Choose one of the following options:
- **Pretrained models provided by OpenSearch**: To learn more, see [OpenSearch-provided pretrained models]({{site.url}}{{site.baseurl}}/ml-commons-plugin/pretrained-models/). For a list of supported models, see [Supported pretrained models]({{site.url}}{{site.baseurl}}/ml-commons-plugin/pretrained-models/#supported-pretrained-models).
- **Custom models** such as PyTorch deep learning models: To learn more, see [Custom models](http://localhost:4000/docs/latest/ml-commons-plugin/custom-local-models/).
## GPU acceleration
For better performance, you can take advantage of GPU acceleration on your ML node. For more information, see [GPU acceleration]({{site.url}}{{site.baseurl}}/ml-commons-plugin/gpu-acceleration/).