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docs/clearml_sdk/task_sdk.md
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@ -671,8 +671,8 @@ task.connect(params_dictionary)
### Configuration Objects
Configuration objects 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.
To log configuration more elaborate than a key-value dictionary (such as nested dictionaries or configuration files),
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).
```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
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).
ClearML can be configured to upload artifacts to any of the supported types of storage, which include local and shared