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2
docs/clearml_data/clearml_data_cli.md
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@ -68,7 +68,7 @@ clearml-data add [-h] [--id ID] [--dataset-folder DATASET_FOLDER]
|`--id` | Dataset's ID. Default: previously created / accessed dataset| <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--files`| Files / folders to add. Items will be uploaded to the dataset's designated storage. | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--wildcard`| Add specific set of files, denoted by these wildcards. For example: `~/data/*.jpg ~/data/json`. Multiple wildcards can be passed. | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--links`| Files / folders link to add. Supports S3, GS, Azure links. Example: `s3://bucket/data` `azure://bucket/folder`. Items remain in their original location. | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--links`| Files / folders link to add. Supports S3, GS, Azure links. Example: `s3://bucket/data` `azure://<account name>.blob.core.windows.net/path/to/file`. Items remain in their original location. | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--dataset-folder` | Dataset base folder to add the files to in the dataset. Default: dataset root| <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--non-recursive` | Disable recursive scan of files | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" /> |
|`--verbose` | Verbose reporting | <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|

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docs/clearml_data/clearml_data_sdk.md
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@ -62,7 +62,7 @@ and auto-increments the version number.
:::
Use the `output_uri` parameter to specify a network storage target to upload the dataset files, and associated information
(such as previews) to (e.g. `s3://bucket/data`, `gs://bucket/data`, `azure://bucket/data`, `file:///mnt/share/data`).
(such as previews) to (e.g. `s3://bucket/data`, `gs://bucket/data`, `azure://<account name>.blob.core.windows.net/path/to/file`, `file:///mnt/share/data`).
By default, the dataset uploads to ClearML's file server. The `output_uri` parameter of the [`Dataset.upload`](#uploading-files)
method overrides this parameter's value.
@ -248,7 +248,7 @@ dataset.get_logger().report_histogram(
To upload the dataset files to network storage, use the [`Dataset.upload`](../references/sdk/dataset.md#upload) method.
Use the `output_url` parameter to specify storage target, such as S3 / GS / Azure (e.g. `s3://bucket/data`, `gs://bucket/data`, `azure://bucket/data`, `/mnt/share/data`).
Use the `output_url` parameter to specify storage target, such as S3 / GS / Azure (e.g. `s3://bucket/data`, `gs://bucket/data`, `azure://<account name>.blob.core.windows.net/path/to/file`, `/mnt/share/data`).
By default, the dataset uploads to ClearML's file server. This target storage overrides the `output_uri` value of the
[`Dataset.create`](#creating-datasets) method.

2
docs/clearml_sdk/task_sdk.md
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@ -659,7 +659,7 @@ For example:
`s3://`, `gs://`, or `azure://`). The artifact will only be added as a URL and will not be uploaded.
```python
task.upload_artifact(name='link', artifact_object='azure://bucket/folder')
task.upload_artifact(name='link', artifact_object='azure://<account name>.blob.core.windows.net/path/to/file')
```
* Serialize and upload a Python object. ClearML automatically chooses the file format based on the object's type, or you

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docs/clearml_serving/clearml_serving_tutorial.md
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@ -104,7 +104,7 @@ or with the `clearml-serving` CLI.
:::info Model Storage
You can also provide a different storage destination for the model, such as S3/GS/Azure, by passing
`--destination="s3://bucket/folder"`, `gs://bucket/folder`, `azure://bucket/folder`. There is no need to provide a unique
`--destination="s3://bucket/folder"`, `gs://bucket/folder`, `azure://<account name>.blob.core.windows.net/path/to/file`. There is no need to provide a unique
path to the destination argument, the location of the model will be a unique path based on the serving service ID and the
model name
:::

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docs/webapp/webapp_exp_tuning.md
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@ -87,7 +87,7 @@ and formats for specifying locations include:
* A shared folder: `/mnt/share/folder`
* S3: `s3://bucket/folder`
* Google Cloud Storage: `gs://bucket-name/folder`
* Azure Storage: `azure://company.blob.core.windows.net/folder/`
* Azure Storage: `azure://<account name>.blob.core.windows.net/path/to/file`
**To add, change, or delete an artifact output destination:**