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docs: Fix links (#5153)
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Fix links

Signed-off-by: Sherlock113 <[email protected]>
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Sherlock113 authored Dec 26, 2024
1 parent 749f49e commit d518de6
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2 changes: 1 addition & 1 deletion docs/source/examples/mlflow.rst
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Expand Up @@ -41,7 +41,7 @@ This example uses the ``scikit-learn`` framework to train a classification model
model.fit(X_train, Y_train)
mlflow.sklearn.save_model(model, model_uri.resolve())
Next, use the ``bentoml.mlflow.import_model`` API to save the model to the BentoML :doc:`/build-with-bentoml/model-loading-and-management`, a local directory to store and manage models. You can retrieve this model later in other services to run predictions.
Next, use the ``bentoml.mlflow.import_model`` API to save the model to the BentoML :doc:`Model Store </build-with-bentoml/model-loading-and-management>`, a local directory to store and manage models. You can retrieve this model later in other services to run predictions.

.. code-block:: bash
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2 changes: 1 addition & 1 deletion docs/source/examples/xgboost.rst
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Expand Up @@ -49,7 +49,7 @@ This example uses the ``scikit-learn`` framework to load and preprocess the `bre
# Train the model
model = xgb.train(param, dt)
After training, use the ``bentoml.xgboost.save_model`` API to save the model to the BentoML :doc:`/build-with-bentoml/model-loading-and-management`, a local directory to store and manage models. You can retrieve this model later in other services to run predictions.
After training, use the ``bentoml.xgboost.save_model`` API to save the model to the BentoML :doc:`Model Store </build-with-bentoml/model-loading-and-management>`, a local directory to store and manage models. You can retrieve this model later in other services to run predictions.

.. code-block:: bash
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