Small edits (#697)

docs/integrations/mmcv.md

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+---
+title: MMCV
+---
+
+:::tip
+If you are not already using ClearML, see [Getting Started](../getting_started/ds/ds_first_steps.md) for setup 
+instructions.
+:::
+
+[MMCV](https://github.com/open-mmlab/mmcv) is a computer vision framework developed by OpenMMLab. You can integrate ClearML into your 
+code using the `mmcv` package's [`ClearMLLoggerHook`](https://mmcv.readthedocs.io/en/master/_modules/mmcv/runner/hooks/logger/clearml.html)
+class. This class is used to create a ClearML Task and to automatically log metrics. 
+
+For example, the following code sets up the configuration for logging metrics periodically to ClearML, and then registers
+the ClearML hook to a [runner](https://mmcv.readthedocs.io/en/v1.3.8/runner.html?highlight=register_training_hooks#epochbasedrunner),
+which manages training in `mmcv`:
+
+```python
+log_config = dict(
+    interval=100,
+    hooks=[
+        dict(
+            type='ClearMLLoggerHook',
+            init_kwargs=dict(
+                project_name='examples',
+                task_name='OpenMMLab cifar10',
+                output_uri=True
+            )
+        ),
+    ]
+)
+
+# register hooks to runner and those hooks will be invoked automatically
+runner.register_training_hooks(
+    lr_config=lr_config,
+    optimizer_config=optimizer_config,
+    checkpoint_config=checkpoint_config,
+    log_config=log_config # ClearMLLogger hook
+)
+```
+
+The `init_kwargs` dictionary can include any parameter from [`Task.init()`](../references/sdk/task.md#taskinit). 
+
+This creates a [ClearML Task](../fundamentals/task.md) `OpenMMLab cifar10` in the `examples` project.
+You can view the captured metrics in the experiment's **Scalars** tab in the [WebApp](../webapp/webapp_overview.md).
+
+![OpenMMLab scalars](../img/itegration_openmmlab_scalars.png)
+
+See MMCV code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/openmmlab/openmmlab_cifar10.py).