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docs/faq.md
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@ -381,7 +381,7 @@ After thirty minutes, it remains unchanged.
Yes! ClearML allows you to control automatic logging for `stdout`, `stderr`, and frameworks when initializing a Task
by calling the [`Task.init`](references/sdk/task.md#taskinit) method.
To control a Task's framework logging, use the `auto_connect_framworks`. Turn off all automatic logging by setting the
To control a Task's framework logging, use the `auto_connect_framworks` parameter. Turn off all automatic logging by setting the
parameter to `False`. For finer grained control of logged frameworks, input a dictionary, with framework-boolean pairs.
For example:

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docs/getting_started/ds/ds_first_steps.md
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@ -26,14 +26,14 @@ In ClearML, experiments are organized as [Tasks](../../fundamentals/task).
ClearML will automatically log your experiment and code, including outputs and parameters from popular ML frameworks,
once you integrate the ClearML [SDK](../../clearml_sdk.md) with your code. To control what ClearML automatically logs, see this [FAQ](../../faq.md#controlling_logging).
At the beginning of your code, import the `clearml` package
At the beginning of your code, import the `clearml` package:
```python
from clearml import Task
```
:::note Full Automatic Logging
To ensure full automatic logging it is recommended to import the ClearML package at the top of your entry script.
To ensure full automatic logging, it is recommended to import the ClearML package at the top of your entry script.
:::
Then initialize the Task object in your `main()` function, or the beginning of the script.