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docs/integrations/yolov5.md
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@ -141,7 +141,7 @@ ClearML dataset page: https://app.clear.mli/datasets/simple/<project-id>/experim
New dataset created id=<dataset-id> New dataset created id=<dataset-id>
``` ```
### Run Training Using A ClearML Dataset ### Run Training Using a ClearML Dataset
Now that you have a ClearML dataset, you can very simply use it to train custom YOLOv5 models: Now that you have a ClearML dataset, you can very simply use it to train custom YOLOv5 models:
```commandline ```commandline
@ -167,7 +167,7 @@ agents on new remote machines in the cloud of your choice (AWS, GCP, Azure): The
shuts down instances as needed, according to the budget that you set. shuts down instances as needed, according to the budget that you set.
### Cloning, Editing, And Enqueuing ### Cloning, Editing, and Enqueuing
![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif) ![Cloning, editing, enqueuing gif](../img/gif/integrations_yolov5.gif)
@ -179,7 +179,7 @@ with the new details on a remote machine:
The ClearML Agent executing the task will use the new values to [override any hard coded values](../clearml_agent.md). The ClearML Agent executing the task will use the new values to [override any hard coded values](../clearml_agent.md).
### Executing A Task Remotely ### Executing a Task Remotely
You can set a task to be executed remotely programmatically by adding `Task.execute_remotely()` to your script. This You can set a task to be executed remotely programmatically by adding `Task.execute_remotely()` to your script. This
method stops the current local execution of the task, and then enqueues it to a specified queue to re-run it on a remote machine. method stops the current local execution of the task, and then enqueues it to a specified queue to re-run it on a remote machine.

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docs/webapp/webapp_reports.md
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@ -100,7 +100,6 @@ resources will be displayed. See [Dynamic Queries](#dynamic-queries) below.
* `min_value` * `min_value`
* `max_value` * `max_value`
* `value` (last value) * `value` (last value)
* `models` - Model IDs. Specify multiple IDs like this: `models=<id>&models=<id>&models<id>`.
* `metrics` - Metric name * `metrics` - Metric name
* `variants` - Variant’s name * `variants` - Variant’s name
* `company` - Workspace ID. Applicable to the ClearML hosted service, for embedding content from a different workspace * `company` - Workspace ID. Applicable to the ClearML hosted service, for embedding content from a different workspace