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4
docs/clearml_agent.md
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@ -17,7 +17,7 @@ title: ClearML Agent
**ClearML Agent** is a virtual environment and execution manager for DL / ML solutions on GPU machines. It integrates with the **ClearML Python Package** and ClearML Server to provide a full AI cluster solution. <br/>
Its main focus is around:
- Reproducing tasks, including their complete environments.
- Reproducing task runs, including their complete environments.
- Scaling workflows on multiple target machines.
ClearML Agent executes a task or other workflow by reproducing the state of the code from the original machine
@ -46,7 +46,7 @@ install Python, so make sure to use a container or environment with the version
While the agent is running, it continuously reports system metrics to the ClearML Server (these can be monitored in the
[**Orchestration**](webapp/webapp_workers_queues.md) page).
Continue using ClearML Agent once it is running on a target machine. Reproduce tasks and execute
Continue using ClearML Agent once it is running on a target machine. Reproducing task runs and execute
automated workflows in one (or both) of the following ways:
* Programmatically (using [`Task.enqueue()`](references/sdk/task.md#taskenqueue) or [`Task.execute_remotely()`](references/sdk/task.md#execute_remotely))
* Through the ClearML Web UI (without working directly with code), by cloning tasks and enqueuing them to the

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docs/getting_started/remote_execution.md
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@ -14,7 +14,7 @@ powerful remote machine. This is useful for:
* Managing execution through ClearML's queue system.
This guide focuses on transitioning a locally executed process to a remote machine for scalable execution. To learn how
to reproduce a previously executed process on a remote machine, see [Reproducing Tasks](reproduce_tasks.md).
to reproduce a previously executed process on a remote machine, see [Reproducing Task Runs](reproduce_tasks.md).
## Running a Task Remotely

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docs/getting_started/reproduce_tasks.md
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@ -1,5 +1,5 @@
---
title: Reproducing Tasks
title: Reproducing Task Runs
---
:::note

27
docs/guides/frameworks/keras/jupyter.md
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@ -18,22 +18,26 @@ The example does the following:
The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots, which are titled **:monitor: machine**.
![image](../../../img/examples_keras_jupyter_08.png)
![Scalars](../../../img/examples_keras_jupyter_08.png#light-mode-only)
![Scalars](../../../img/examples_keras_jupyter_08_dark.png#dark-mode-only)
## Plots
The example calls Matplotlib methods to create several sample plots, and TensorBoard methods to plot histograms for layer density.
They appear in **PLOTS**.
![image](../../../img/examples_keras_jupyter_03.png)
![Plots 1](../../../img/examples_keras_jupyter_03.png#light-mode-only)
![Plots 1](../../../img/examples_keras_jupyter_03_dark.png#dark-mode-only)
![image](../../../img/examples_keras_jupyter_03a.png)
![Plots 2](../../../img/examples_keras_jupyter_03a.png#light-mode-only)
![Plots 2](../../../img/examples_keras_jupyter_03a_dark.png#dark-mode-only)
## Debug Samples
The example calls Matplotlib methods to log debug sample images. They appear in **DEBUG SAMPLES**.
![image](../../../img/examples_keras_jupyter_04.png)
![Debug Samples](../../../img/examples_keras_jupyter_04.png#light-mode-only)
![Debug Samples](../../../img/examples_keras_jupyter_04_dark.png#dark-mode-only)
## Hyperparameters
@ -55,17 +59,20 @@ task_params['hidden_dim'] = 512
Parameter dictionaries appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **General**.
![image](../../../img/examples_keras_jupyter_20.png)
![General Hyperparameters](../../../img/examples_keras_jupyter_20.png#light-mode-only)
![General Hyperparameters](../../../img/examples_keras_jupyter_20_dark.png#dark-mode-only)
The TensorFlow Definitions appear in the **TF_DEFINE** subsection.
![image](../../../img/examples_keras_jupyter_21.png)
![TF Define](../../../img/examples_keras_jupyter_21.png#light-mode-only)
![TF Define](../../../img/examples_keras_jupyter_21_dark.png#dark-mode-only)
## Console
Text printed to the console for training appears in **CONSOLE**.
![image](../../../img/examples_keras_jupyter_07.png)
![Console Log](../../../img/examples_keras_jupyter_07.png#light-mode-only)
![Console Log](../../../img/examples_keras_jupyter_07_dark.png#dark-mode-only)
## Artifacts
@ -74,9 +81,11 @@ created using Keras.
The task info panel shows model tracking, including the model name and design in **ARTIFACTS** **>** **Output Model**.
![image](../../../img/examples_keras_jupyter_23.png)
![Artifacts](../../../img/examples_keras_jupyter_23.png#light-mode-only)
![Artifacts](../../../img/examples_keras_jupyter_23_dark.png#dark-mode-only)
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can view
the model's details and access the model.
![image](../../../img/examples_keras_jupyter_24.png)
![Model details](../../../img/examples_keras_jupyter_24.png#light-mode-only)
![Model details](../../../img/examples_keras_jupyter_24_dark.png#dark-mode-only)

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docs/guides/frameworks/keras/keras_tensorboard.md
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@ -25,31 +25,36 @@ The example script does the following:
The loss and accuracy metric scalar plots appear in **SCALARS**, along with the resource utilization plots,
which are titled **:monitor: machine**.
![image](../../../img/examples_keras_01.png)
![Scalars](../../../img/examples_keras_01.png#light-mode-only)
![Scalars](../../../img/examples_keras_01_dark.png#dark-mode-only)
## Histograms
Histograms for layer density appear in **PLOTS**.
![image](../../../img/examples_keras_02.png)
![Histograms](../../../img/examples_keras_02.png#light-mode-only)
![Histograms](../../../img/examples_keras_02_dark.png#dark-mode-only)
## Hyperparameters
ClearML automatically logs command line options generated with `argparse`, and TensorFlow Definitions.
ClearML automatically logs command line options generated with `argparse` and TensorFlow Definitions.
Command line options appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **Args**.
![image](../../../img/examples_keras_00.png)
![Hyperparameters Args](../../../img/examples_keras_00.png#light-mode-only)
![Hyperparameters Args](../../../img/examples_keras_00_dark.png#dark-mode-only)
TensorFlow Definitions appear in **TF_DEFINE**.
![image](../../../img/examples_keras_00a.png)
![TF Defines](../../../img/examples_keras_00a.png#light-mode-only)
![TF Defines](../../../img/examples_keras_00a_dark.png#dark-mode-only)
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
![image](../../../img/keras_colab_01.png)
![Console Log](../../../img/keras_colab_01.png#light-mode-only)
![Console Log](../../../img/keras_colab_01_dark.png#dark-mode-only)
## Configuration Objects
@ -64,4 +69,5 @@ task.connect_configuration(
It appears in **CONFIGURATION** **>** **CONFIGURATION OBJECTS** **>** **MyConfig**.
![image](../../../img/keras_colab_02.png)
![Custom configuration](../../../img/keras_colab_02.png#light-mode-only)
![Custom configuration](../../../img/keras_colab_02_dark.png#dark-mode-only)

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docs/guides/frameworks/scikit-learn/sklearn_joblib_example.md
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@ -12,16 +12,19 @@ and `matplotlib` to create a scatter diagram. When the script runs, it creates a
ClearML automatically logs the scatter plot, which appears in the [task's page](../../../webapp/webapp_exp_track_visual.md)
in the ClearML web UI, under **PLOTS**.
![image](../../../img/examples_sklearn_joblib_example_06.png)
![Plots](../../../img/examples_sklearn_joblib_example_06.png#light-mode-only)
![Plots](../../../img/examples_sklearn_joblib_example_06_dark.png#dark-mode-only)
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab.
![image](../../../img/examples_sklearn_joblib_example_01.png)
![Artifacts](../../../img/examples_sklearn_joblib_example_01.png#light-mode-only)
![Artifacts](../../../img/examples_sklearn_joblib_example_01_dark.png#dark-mode-only)
Clicking on the model name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can
view the model's details and access the model.
![image](../../../img/examples_sklearn_joblib_example_02.png)
![Model details](../../../img/examples_sklearn_joblib_example_02.png#light-mode-only)
![Model details](../../../img/examples_sklearn_joblib_example_02_dark.png#dark-mode-only)

15
docs/guides/frameworks/tensorboardx/tensorboardx.md
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@ -16,30 +16,35 @@ The script does the following:
The loss and accuracy metric scalar plots appear in the task's page in the **ClearML web UI**, under
**SCALARS**. The also includes resource utilization plots, which are titled **:monitor: machine**.
![image](../../../img/examples_pytorch_tensorboardx_03.png)
![Scalars](../../../img/examples_pytorch_tensorboardx_03.png#light-mode-only)
![Scalars](../../../img/examples_pytorch_tensorboardx_03_dark.png#dark-mode-only)
## Hyperparameters
ClearML automatically logs command line options defined with `argparse`. They appear in **CONFIGURATION** **>**
**HYPERPARAMETERS** **>** **Args**.
![image](../../../img/examples_pytorch_tensorboardx_01.png)
![Hyperparameters](../../../img/examples_pytorch_tensorboardx_01.png#light-mode-only)
![Hyperparameters](../../../img/examples_pytorch_tensorboardx_01_dark.png#dark-mode-only)
## Console
Text printed to the console for training progress, as well as all other console output, appear in **CONSOLE**.
![image](../../../img/examples_pytorch_tensorboardx_02.png)
![Console log](../../../img/examples_pytorch_tensorboardx_02.png#light-mode-only)
![Console log](../../../img/examples_pytorch_tensorboardx_02_dark.png#dark-mode-only)
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models and any snapshots created using PyTorch.
![image](../../../img/examples_pytorch_tensorboardx_04.png)
![Artifacts](../../../img/examples_pytorch_tensorboardx_04.png#light-mode-only)
![Artifacts](../../../img/examples_pytorch_tensorboardx_04_dark.png#dark-mode-only)
Clicking on the model's name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can
view the model's details and access the model.
![image](../../../img/examples_pytorch_tensorboardx_model.png)
![Model details](../../../img/examples_pytorch_tensorboardx_model.png#light-mode-only)
![Model details](../../../img/examples_pytorch_tensorboardx_model_dark.png#dark-mode-only)

3
docs/guides/frameworks/tensorboardx/video_tensorboardx.md
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@ -14,5 +14,6 @@ the `examples` project.
ClearML automatically captures the video data that is added to the `SummaryWriter` object, using the `add_video` method.
The video appears in the task's **DEBUG SAMPLES** tab.
![Debug Samples](../../../img/examples_tensorboardx_debug.png)
![Debug Samples](../../../img/examples_tensorboardx_debug.png#light-mode-only)
![Debug Samples](../../../img/examples_tensorboardx_debug_dark.png#dark-mode-only)

21
docs/guides/frameworks/tensorflow/integration_keras_tuner.md
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@ -44,28 +44,33 @@ When the script runs, it logs:
ClearML logs the scalars from training each network. They appear in the task's page in the **ClearML web UI**, under
**SCALARS**.
![image](../../../img/integration_keras_tuner_06.png)
![Scalars](../../../img/integration_keras_tuner_06.png#light-mode-only)
![Scalars](../../../img/integration_keras_tuner_06_dark.png#dark-mode-only)
## Summary of Hyperparameter Optimization
ClearML automatically logs the parameters of each task run in the hyperparameter search. They appear in tabular
form in **PLOTS**.
![image](../../../img/integration_keras_tuner_07.png)
![HPO summary plot](../../../img/integration_keras_tuner_07.png#light-mode-only)
![HPO summary plot](../../../img/integration_keras_tuner_07_dark.png#dark-mode-only)
## Artifacts
ClearML automatically stores the output model. It appears in **ARTIFACTS** **>** **Output Model**.
![image](../../../img/integration_keras_tuner_03.png)
![Artifact](../../../img/integration_keras_tuner_03.png#light-mode-only)
![Artifact](../../../img/integration_keras_tuner_03_dark.png#dark-mode-only)
Model details, such as snap locations, appear in the **MODELS** tab.
![image](../../../img/integration_keras_tuner_04.png)
![Model details](../../../img/integration_keras_tuner_04.png#light-mode-only)
![Model details](../../../img/integration_keras_tuner_04_dark.png#dark-mode-only)
The model configuration is stored with the model.
![image](../../../img/integration_keras_tuner_05.png)
![Model configuration](../../../img/integration_keras_tuner_05.png#light-mode-only)
![Model configuration](../../../img/integration_keras_tuner_05_dark.png#dark-mode-only)
## Configuration Objects
@ -73,12 +78,14 @@ The model configuration is stored with the model.
ClearML automatically logs the TensorFlow Definitions, which appear in **CONFIGURATION** **>** **HYPERPARAMETERS**.
![image](../../../img/integration_keras_tuner_01.png)
![Hyperparameters](../../../img/integration_keras_tuner_01.png#light-mode-only)
![Hyperparameters](../../../img/integration_keras_tuner_01_dark.png#dark-mode-only)
### Configuration
The Task configuration appears in **CONFIGURATION** **>** **General**.
![image](../../../img/integration_keras_tuner_02.png)
![Configuration object](../../../img/integration_keras_tuner_02.png#light-mode-only)
![Configuration object](../../../img/integration_keras_tuner_02_dark.png#dark-mode-only)

17
docs/guides/frameworks/tensorflow/tensorboard_pr_curve.md
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@ -20,24 +20,29 @@ In the **ClearML Web UI**, the PR Curve summaries appear in the task's page unde
* Blue PR curves
![image](../../../img/examples_tensorboard_pr_curve_01.png)
![Blue PR curves](../../../img/examples_tensorboard_pr_curve_01.png#light-mode-only)
![Blue PR curves](../../../img/examples_tensorboard_pr_curve_01_dark.png#dark-mode-only)
* Green PR curves
![image](../../../img/examples_tensorboard_pr_curve_02.png)
![Green PR curves](../../../img/examples_tensorboard_pr_curve_02.png#light-mode-only)
![Green PR curves](../../../img/examples_tensorboard_pr_curve_02_dark.png#dark-mode-only)
* Red PR curves
![image](../../../img/examples_tensorboard_pr_curve_03.png)
![Red PR curves](../../../img/examples_tensorboard_pr_curve_03.png#light-mode-only)
![Red PR curves](../../../img/examples_tensorboard_pr_curve_03_dark.png#dark-mode-only)
## Hyperparameters
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **TF_DEFINE**.
![image](../../../img/examples_tensorboard_pr_curve_04.png)
![Hyperparameters](../../../img/examples_tensorboard_pr_curve_04.png#light-mode-only)
![Hyperparameters](../../../img/examples_tensorboard_pr_curve_04_dark.png#dark-mode-only)
## Console
All other console output appears in **CONSOLE**.
All console output appears in **CONSOLE** tab.
![image](../../../img/examples_tensorboard_pr_curve_05.png)
![Console log](../../../img/examples_tensorboard_pr_curve_05.png#light-mode-only)
![Console log](../../../img/examples_tensorboard_pr_curve_05_dark.png#dark-mode-only)

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docs/guides/frameworks/tensorflow/tensorboard_toy.md
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@ -14,25 +14,29 @@ project.
The `tf.summary.scalar` output appears in the ClearML web UI, in the task's
**SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
![image](../../../img/examples_tensorboard_toy_03.png)
![Scalars](../../../img/examples_tensorboard_toy_03.png#light-mode-only)
![Scalars](../../../img/examples_tensorboard_toy_03_dark.png#dark-mode-only)
## Plots
The `tf.summary.histogram` output appears in **PLOTS**.
![image](../../../img/examples_tensorboard_toy_04.png)
![Plots](../../../img/examples_tensorboard_toy_04.png#light-mode-only)
![Plots](../../../img/examples_tensorboard_toy_04_dark.png#dark-mode-only)
## Debug Samples
ClearML automatically tracks images and text output to TensorFlow. They appear in **DEBUG SAMPLES**.
![image](../../../img/examples_tensorboard_toy_05.png)
![Debug Samples](../../../img/examples_tensorboard_toy_05.png#light-mode-only)
![Debug Samples](../../../img/examples_tensorboard_toy_05_dark.png#dark-mode-only)
## Hyperparameters
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>**
**TF_DEFINE**.
![image](../../../img/examples_tensorboard_toy_01.png)
![Hyperparameters](../../../img/examples_tensorboard_toy_01.png#light-mode-only)
![Hyperparameters](../../../img/examples_tensorboard_toy_01_dark.png#dark-mode-only)

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docs/guides/frameworks/tensorflow/tensorflow_mnist.md
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@ -13,30 +13,35 @@ When the script runs, it creates a task named `Tensorflow v2 mnist with summarie
The loss and accuracy metric scalar plots appear in the task's page in the **ClearML web UI** under
**SCALARS**. Resource utilization plots, which are titled **:monitor: machine**, also appear in the **SCALARS** tab.
![Task scalars](../../../img/examples_tensorflow_mnist_06.png)
![Task scalars](../../../img/examples_tensorflow_mnist_06.png#light-mode-only)
![Task scalars](../../../img/examples_tensorflow_mnist_06_dark.png#dark-mode-only)
## Hyperparameters
ClearML automatically logs TensorFlow Definitions. They appear in **CONFIGURATION** **>** **HYPERPARAMETERS**
**>** **TF_DEFINE**.
![Task hyperparameters](../../../img/examples_tensorflow_mnist_01.png)
![Task hyperparameters](../../../img/examples_tensorflow_mnist_01.png#light-mode-only)
![Task hyperparameters](../../../img/examples_tensorflow_mnist_01_dark.png#dark-mode-only)
## Console
All console output appears in **CONSOLE**.
![Task console](../../../img/examples_tensorflow_mnist_05.png)
![Task console](../../../img/examples_tensorflow_mnist_05.png#light-mode-only)
![Task console](../../../img/examples_tensorflow_mnist_05_dark.png#dark-mode-only)
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models and any snapshots created using TensorFlow.
![Task models](../../../img/examples_tensorflow_mnist_03.png)
![Task models](../../../img/examples_tensorflow_mnist_03.png#light-mode-only)
![Task models](../../../img/examples_tensorflow_mnist_03_dark.png#dark-mode-only)
Clicking on a model's name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can
view the model's details and access the model.
![Model details](../../../img/examples_tensorflow_mnist_10.png)
![Model details](../../../img/examples_tensorflow_mnist_10.png#light-mode-only)
![Model details](../../../img/examples_tensorflow_mnist_10_dark.png#dark-mode-only)

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docs/guides/frameworks/xgboost/xgboost_metrics.md
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@ -13,7 +13,8 @@ the `examples` project.
ClearML automatically captures scalars logged with XGBoost, which can be visualized in plots in the
ClearML WebApp, in the task's **SCALARS** tab.
![Scalars](../../../img/examples_xgboost_metric_scalars.png)
![Scalars](../../../img/examples_xgboost_metric_scalars.png#light-mode-only)
![Scalars](../../../img/examples_xgboost_metric_scalars_dark.png#dark-mode-only)
## Models
@ -21,14 +22,17 @@ ClearML automatically captures the model logged using the `xgboost.save` method,
View saved snapshots in the task's **ARTIFACTS** tab.
![Artifacts tab](../../../img/examples_xgboost_metric_artifacts.png)
![Artifacts tab](../../../img/examples_xgboost_metric_artifacts.png#light-mode-only)
![Artifacts tab](../../../img/examples_xgboost_metric_artifacts_dark.png#dark-mode-only)
To view the model details, click the model name in the **ARTIFACTS** page, which will open the model's info tab. Alternatively, download the model.
![Model info panel](../../../img/examples_xgboost_metric_model.png)
![Model info panel](../../../img/examples_xgboost_metric_model.png#light-mode-only)
![Model info panel](../../../img/examples_xgboost_metric_model_dark.png#dark-mode-only)
## Console
All console output during the script's execution appears in the task's **CONSOLE** page.
![Console output](../../../img/examples_xgboost_metric_console.png)
![Console output](../../../img/examples_xgboost_metric_console.png#light-mode-only)
![Console output](../../../img/examples_xgboost_metric_console_dark.png#dark-mode-only)

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docs/guides/frameworks/xgboost/xgboost_sample.md
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@ -18,25 +18,30 @@ classification dataset using XGBoost
The feature importance plot and tree plot appear in the task's page in the **ClearML web UI**, under
**PLOTS**.
![Feature importance plot](../../../img/examples_xgboost_sample_06.png)
![Feature importance plot](../../../img/examples_xgboost_sample_06.png#light-mode-only)
![Feature importance plot](../../../img/examples_xgboost_sample_06_dark.png#dark-mode-only)
![Tree plot](../../../img/examples_xgboost_sample_06a.png)
![Tree plot](../../../img/examples_xgboost_sample_06a.png#light-mode-only)
![Tree plot](../../../img/examples_xgboost_sample_06a_dark.png#dark-mode-only)
## Console
All other console output appear in **CONSOLE**.
![image](../../../img/examples_xgboost_sample_05.png)
![Console log](../../../img/examples_xgboost_sample_05.png#light-mode-only)
![Console log](../../../img/examples_xgboost_sample_05_dark.png#dark-mode-only)
## Artifacts
Models created by the task appear in the task's **ARTIFACTS** tab. ClearML automatically logs and tracks
models and any snapshots created using XGBoost.
![image](../../../img/examples_xgboost_sample_10.png)
![Artifacts](../../../img/examples_xgboost_sample_10.png#light-mode-only)
![Artifacts](../../../img/examples_xgboost_sample_10_dark.png#dark-mode-only)
Clicking on the model's name takes you to the [model's page](../../../webapp/webapp_model_viewing.md), where you can
view the model's details and access the model.
![image](../../../img/examples_xgboost_sample_03.png)
![Model details](../../../img/examples_xgboost_sample_03.png#light-mode-only)
![Model details](../../../img/examples_xgboost_sample_03_dark.png#dark-mode-only)

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