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docs/source/user_guide/model_registration/frameworks/huggingfacemodel.rst

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deployment_log_group_id = log_group_id,
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deployment_access_log_id = log_id,
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deployment_predict_log_id = log_id)
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zero_shot_image_classification_model.predict(image)
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zero_shot_image_classification_model.predict(data)
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zero_shot_image_classification_model.predict(body)
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### Invoke the model by sending bytes

docs/source/user_guide/model_training/automl/index.rst

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==============
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.. note::
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Working with AutoML has moved from within ADS to working directly with the AutoMLx library.
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AutoMLx is under active development, and will be expanding into areas of explainability, fairness and deep learning.
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To offer this functionality, the best way is for the ADS to work together as separate libraries.
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AutoMLx are preinstalled in conda pack automlx_p38_cpu_v#, and can now be updated independently of ADS. AutoMLx documentation may be found at `this link <https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html>`__.
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Notebook examples are in `Oracle's samples repository <https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples>`__ and a migration tutorial can be found at :doc:`../../../user_guide/model_training/automl/quick_start` section.
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Building Oracle AutoMLx models starting with oracle-ads 2.8.2, is now performed directly with the AutoMLx library.
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AutoMLx documentation can be found `here <https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html>`__.
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Oracle AutoMLx is installed in the conda pack `automlx_p38_cpu_v#`.
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Notebook examples are `here <https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples>`__ and a migration tutorial can be found in the :doc:`../../../user_guide/model_training/automl/quick_start` section.
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.. toctree::
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