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feat: update prebuilt models documentation #3186

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Empty file removed doc/doc_utils/jumpstart.rst
Empty file.
19 changes: 12 additions & 7 deletions doc/doc_utils/jumpstart_doc_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -143,20 +143,25 @@ def create_jumpstart_model_table():
file_content.append(".. |external-link| raw:: html\n\n")
file_content.append(' <i class="fa fa-external-link"></i>\n\n')

file_content.append("==================================\n")
file_content.append("JumpStart Available Model Table\n")
file_content.append("==================================\n")
file_content.append("================================================\n")
file_content.append("Built-in Algorithms with pre-trained Model Table\n")
file_content.append("================================================\n")
file_content.append(
"""
JumpStart for the SageMaker Python SDK uses model IDs and model versions to access the necessary
utilities. This table serves to provide the core material plus some extra information that can be useful
in selecting the correct model ID and corresponding parameters.\n"""
The SageMaker Python SDK uses model IDs and model versions to access the necessary
utilities for pre-trained models. This table serves to provide the core material plus
some extra information that can be useful in selecting the correct model ID and
corresponding parameters.\n"""
)
file_content.append(
"""
If you want to automatically use the latest version of the model, use "*" for the `model_version` attribute.
We highly suggest pinning an exact model version however.\n"""
)
file_content.append(
"""
These models are also available through the `JumpStart UI in SageMaker Studio <https://docs.aws.amazon.com/sagemaker/latest/dg/studio-jumpstart.html>`__\n"""
)
file_content.append("\n")
file_content.append(".. list-table:: Available Models\n")
file_content.append(" :widths: 50 20 20 20 30 20\n")
Expand All @@ -183,5 +188,5 @@ def create_jumpstart_model_table():
" - `{} <{}>`__ |external-link|\n".format(model_source, model_spec["url"])
)

f = open("doc_utils/jumpstart.rst", "w")
f = open("doc_utils/pretrainedmodels.rst", "w")
f.writelines(file_content)
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