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4
docs/clearml_sdk/task_sdk.md
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@ -671,8 +671,8 @@ task.connect(params_dictionary)
### Configuration Objects ### Configuration Objects
Configuration objects more elaborate than a key-value dictionary (such as nested dictionaries or configuration files), To log configuration more elaborate than a key-value dictionary (such as nested dictionaries or configuration files),
can be logged to a task using the [`Task.connect_configuration`](../references/sdk/task.md#connect_configuration) method. use the [`Task.connect_configuration`](../references/sdk/task.md#connect_configuration) method.
This method saves configuration objects as blobs (i.e. ClearML is not aware of their internal structure). This method saves configuration objects as blobs (i.e. ClearML is not aware of their internal structure).
```python ```python

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docs/fundamentals/task.md
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@ -67,7 +67,7 @@ Most importantly, ClearML also logs experiments’ input and output models as we
#### Logging Artifacts #### Logging Artifacts
ClearML provides an explicit logging interface that supports manually reporting a variety of artifacts. Any type of ClearML provides an explicit logging interface that supports manually reporting a variety of artifacts. Any type of
artifact can be logged to a task using the [`Task.upload_artifact`](../references/sdk/task.md#upload_artifacts) method. artifact can be logged to a task using the [`Task.upload_artifact`](../references/sdk/task.md#upload_artifact) method.
See more details in the [Artifacts Reporting example](../guides/reporting/artifacts.md). See more details in the [Artifacts Reporting example](../guides/reporting/artifacts.md).
ClearML can be configured to upload artifacts to any of the supported types of storage, which include local and shared ClearML can be configured to upload artifacts to any of the supported types of storage, which include local and shared