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Noam Wasersprung 2025-04-06 10:25:43 +03:00 committed by GitHub
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docs/clearml_serving/clearml_serving_tutorial.md
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@ -7,7 +7,7 @@ In this tutorial, you will go over the model lifecycle -- from training to servi
* Serving the model using **ClearML Serving** * Serving the model using **ClearML Serving**
* Spinning the inference container * Spinning the inference container
The tutorial also covers the following`clearml-serving` features: The tutorial also covers the following `clearml-serving` features:
* Automatic model deployment * Automatic model deployment
* Canary endpoints * Canary endpoints
* Model performance monitoring * Model performance monitoring

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docs/deploying_clearml/enterprise_deploy/change_artifact_links.md
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@ -30,7 +30,7 @@ script changes the values in the databases, and can't be undone.
1. Access the `apiserver` Docker container: 1. Access the `apiserver` Docker container:
* In `docker-compose:` * In `docker-compose`:
```commandline ```commandline
sudo docker exec -it allegro-apiserver /bin/bash sudo docker exec -it allegro-apiserver /bin/bash

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docs/getting_started/data_management.md
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@ -49,7 +49,7 @@ Your goal is to create an immutable copy of the data to be used by further steps
The second step is to preprocess the data. First access the data, then modify it, The second step is to preprocess the data. First access the data, then modify it,
and lastly create a new version of the data. and lastly create a new version of the data.
1. Create a task for you data preprocessing (not required): 1. Create a task for your data preprocessing (not required):
```python ```python
from clearml import Task, Dataset from clearml import Task, Dataset