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Updated diagrams and documentation.
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docs/source/_static/custom.css

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img[alt=pipelines] {
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docs/source/codeflare.pipelines.rst

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CodeFlare Pipelines
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API Documentation
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===========================
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CodeFlare Pipelines Datamodel

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docs/source/index.rst

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:caption: User guide
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pipelines/pipelines_overview
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codeflare.pipelines
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.. toctree::
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![pipelines](../images/pipelines.svg)
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## CodeFlare Pipelines
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CodeFlare Pipelines reimagined pipelines to provide a more intuitive API for the data scientist to create AI/ML pipelines, data workflows, pre-processing, post-processing tasks, and many more which can scale from a laptop to a cluster seamlessly.
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See the API documentation [here](https://codeflare.readthedocs.io/en/latest/codeflare.pipelines.html), and reference use case documentation in the Examples section.
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Examples are provided as execuatble [notebooks](https://github.com/project-codeflare/codeflare/tree/main/notebooks).
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Notebooks can can be run with locally with:
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```shell
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jupyter-lab notebooks/<example_notebook>
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```
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Or, if using any of the recommended cloud based deployments, examples are found in `codeflare/notebooks`, which can be executed directly from Jupyter environment.
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As a first example, we recommend the [sample pipeline](https://github.com/project-codeflare/codeflare/blob/main/notebooks/sample_pipeline.ipynb).

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