Small edits

docs/clearml_agent/clearml_agent_fractional_gpus.md

@@ -80,7 +80,7 @@ For either setup, you can set up in your Enterprise ClearML Agent Helm chart the
 each queue. When a task is enqueued in ClearML, it translates into a Kubernetes pod running on the designated device 
 with the specified fractional resource as defined in the Agent Helm chart. 
 
-#### MIG-enabled GPUs 
+#### MIG-enabled GPUs
 The **ClearML Dynamic MIG Operator** (CDMO) chart enables running AI workloads on K8s with optimized hardware utilization 
 and workload performance by facilitating MIG GPU partitioning. Make sure you have a [MIG capable GPU](https://docs.nvidia.com/datacenter/tesla/mig-user-guide/index.html#supported-gpus).
 

docs/clearml_sdk/clearml_sdk_setup.md

@@ -2,7 +2,7 @@
 title: ClearML Python Package 
 ---
 
-This is step-by-step guide for installing the `clearml` Python package and connecting it to the ClearML Server. Once done,
+This is a step-by-step guide for installing the `clearml` Python package and connecting it to the ClearML Server. Once done,
 you can integrate `clearml` into your code. 
 
 ## Install ClearML

docs/clearml_sdk/task_sdk.md

@@ -74,6 +74,7 @@ After invoking `Task.init` in a script, ClearML starts its automagical logging,
     * [AutoKeras](../integrations/autokeras.md)
     * [CatBoost](../integrations/catboost.md)
     * [Fast.ai](../integrations/fastai.md)
+    * [Hugging Face Transformers](../integrations/transformers.md)
     * [LightGBM](../integrations/lightgbm.md)
     * [MegEngine](../integrations/megengine.md)
     * [MONAI](../integrations/monai.md)

docs/deploying_clearml/clearml_server.md

@@ -4,7 +4,7 @@ title: ClearML Server
 
 ## What is ClearML Server? 
 The ClearML Server is the backend service infrastructure for ClearML. It allows multiple users to collaborate and 
-manage their tasks by working seamlessly with the ClearML Python package and [ClearML Agent](../clearml_agent.md). 
+manage their tasks by working seamlessly with the [ClearML Python package](../clearml_sdk/clearml_sdk_setup.md) and [ClearML Agent](../clearml_agent.md). 
 
 ClearML Server is composed of the following:
 * Web server including the [ClearML Web UI](../webapp/webapp_overview.md), which is the user interface for tracking, comparing, and managing tasks.

docs/deploying_clearml/clearml_server_config.md

@@ -233,7 +233,7 @@ The following example, which is based on AWS load balancing, demonstrates the co
 
 
 
-### Opening Elasticsearch, MongoDB, and Redis for External Access 
+### Opening Elasticsearch, MongoDB, and Redis for External Access
 
 For improved security, the ports for ClearML Server Elasticsearch, MongoDB, and Redis servers are not exposed by default; 
 they are only open internally in the docker network. If external access is needed, open these ports (but make sure to 

docs/deploying_clearml/enterprise_deploy/app_custom.md

@@ -29,12 +29,12 @@ The `General` section is the root-level section of the configuration file, and c
 * `id` - A unique id for the application
 * `name` - The name to display in the web application
 * `version` - The version of the application implementation. Recommended to have three numbers and to bump up when updating applications, so that older running instances can still be displayed
-* `provider` - The person/team/group who is the owner of the application. This will appears in the UI 
+* `provider` - The person/team/group who is the owner of the application. This will appear in the UI 
 * `description` - Short description of the application to be displayed in the ClearML Web UI
 * `icon` (*Optional*) - Small image to display in the ClearML web UI as an icon for the application. Can be a public web url or an image in the application’s assets directory (described below)
 * `no_info_html` (*Optional*) - HTML content to display as a placeholder for the dashboard when no instance is available. Can be a public web url or a file in the application’s assets directory (described below)
 * `default-queue` - The queue to which application instance will be sent when launching a new instance. This queue should have an appropriate agent servicing it. See details in the Custom Apps Agent section below.
-* `badges` (*Optional*) - List of strings to display as a bacge/label in the UI
+* `badges` (*Optional*) - List of strings to display as a badge/label in the UI
 * `resumable` - Boolean indication whether a running application instance can be restarted if required. Default is false.
 * `category` (*Optional*) - Way to separate apps into different tabs in the ClearML web UI
 * `featured` (*Optional*) - Value affecting the order of applications. Lower values are displayed first. Defaults to 500
@@ -264,7 +264,7 @@ The dashboard elements are organized into lines.
 
 The section contains the following information:
 * `lines` - The array of line elements, each containing:
-  * `style` - CSS definitions for the line e.g setting the line height
+  * `style` - CSS definitions for the line e.g. setting the line height
   * `contents` - An array of dashboard elements to display in a given line. Each element may have several fields:
     * `title` - Text to display at the top of the field
     * `type` - one of the following:

docs/getting_started/clearml_agent_scheduling.md

@@ -82,7 +82,7 @@ Currently, these runtime properties can only be set using an ClearML REST API ca
 endpoint, as follows: 
 
 * The body of the request must contain the `worker-id`, and the runtime property to add.
-* An expiry date is optional. Use the format `"expiry":<time>`. For example,  `"expiry":86400` will set an expiry of 24 hours.
+* An expiry date is optional. Use the format `"expiry":<time>`. For example, `"expiry":86400` will set an expiry of 24 hours.
 * To delete the property, set the expiry date to zero, `"expiry":0`.
 
 For example, to force a worker on for 24 hours:

docs/integrations/integrations.md

@@ -8,6 +8,7 @@ ClearML seamlessly integrates with a wide range of popular machine learning fram
 * [Keras](keras.md)
 * [YOLO v5](yolov5.md)
 * [YOLO v8](yolov8.md)
+* [Hugging Face Accelerate](accelerate.md)
 * [Hugging Face Transformers](transformers.md)
 * [MMEngine](mmengine.md)
 * [MMCV](mmcv.md)

docs/release_notes/clearml_server/enterprise/ver_3_24.md

@@ -47,7 +47,7 @@ title: Version 3.24
 * Add UI pipeline DAG presentation with pipeline steps grouped into stages
 * Add Hyper-Dataset version sort by update time in ascending and descending order
 * Add opacity control to Hyper-Dataset frame ROIs 
-* Add search bar for UI Settings's Users and Groups
+* Add search bar for UI Settings' Users and Groups
 * Add number of frames display to UI DataView preview
 * Remove legacy "Augmentation" sections from UI Dataview pages
 * Add control to collapse and expand UI Hyper-Dataset version list

docs/webapp/webapp_overview.md

@@ -79,7 +79,7 @@ specified above and returns results divided by object type (projects, tasks, mod
 :::tip Additional filtering
 ClearML's object tables (e.g. [tasks](webapp_exp_table.md), [models](webapp_model_table.md), [pipelines](pipelines/webapp_pipeline_table.md), 
 and [datasets](datasets/webapp_dataset_page.md)) provide column filters to easily focus your search by object properties
-(e.g status, creation/update time, metric values, etc.).
+(e.g. status, creation/update time, metric values, etc.).
 :::
 
 ### Helpful Resources