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Change terminology (#1028)

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2025-02-06 17:31:11 +02:00
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@@ -23,7 +23,7 @@ You can use the model catalog to trigger CI/CD pipelines based on changes (e.g.
publishing models).
The ClearML SDK makes it easy for colleagues to access others' work and always fetch models based on the model catalog
or the experiment that created the model.
or the task that created the model.
The ClearML web UI visualizes the model catalog for complete observability and lineage of the model lifecycle, providing
governance at scale.
@@ -77,7 +77,7 @@ See [Automatic Logging](clearml_sdk/task_sdk.md#automatic-logging) for more info
### Manual Logging
You can explicitly specify an experiment’s models using ClearML `InputModel` and `OutputModel` classes.
You can explicitly specify a task’s models using ClearML `InputModel` and `OutputModel` classes.
#### InputModel
@@ -101,8 +101,8 @@ input_model_2 = InputModel.import_model(
)
```
After instantiating an InputModel instance, you can connect it to a task object, so the model can be traced to an
experiment.
After instantiating an InputModel instance, you can connect it to a task object, so the model can be traced to n
task.
```python
# Connect the input model to the task
@@ -111,10 +111,10 @@ task.connect(input_model)
#### OutputModel
Use the [`OutputModel`](references/sdk/model_outputmodel.md) class to log your experiment outputs. An OutputModel object
Use the [`OutputModel`](references/sdk/model_outputmodel.md) class to log your task outputs. An OutputModel object
is instantiated with a task object as an argument (see [`task`](references/sdk/model_outputmodel.md) parameter), so it's
registered as the task's output model. Since OutputModel objects are connected to tasks, the models are traceable in
experiments.
tasks.
```python
from clearml import OutputModel, Task
@@ -159,9 +159,9 @@ ClearML models are independent entities facilitating their use in many use cases
You can modify your models’ details via the UI: add metadata, change names, reconfigure, and add/edit label enumeration.
Modified models can be used as input models in your ClearML Tasks.
You can modify the models that an experiment trains:
1. Clone an experiment
1. Go to the experiment's **Artifacts** tab
You can modify the models that a task trains:
1. Clone a task
1. Go to the task's **Artifacts** tab
1. Hover over an input model's `Model name` field and click **Edit**. Then click <img src="/docs/latest/icons/ico-edit.svg" alt="Edit Pencil" className="icon size-md" />.
This will open up a window with a model table, where you can select any model from the model catalog.