You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on Jul 14, 2025. It is now read-only.
Copy file name to clipboardExpand all lines: MIGRATION_TO_MLM.md
+3-3Lines changed: 3 additions & 3 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -37,8 +37,8 @@ Both the ML Model Extension and the Machine Learning Model (MLM) Extension aim t
37
37
Notable differences:
38
38
39
39
- The MLM Extension covers more details at both the Item and Asset levels, making it easier to describe and use model metadata.
40
-
- The MLM Extension covers Runtime requirements within the [Container Asset](https://github.com/crim-ca/mlm-extension?tab=readme-ov-file#container-asset), while the ML Model Extension records [similar information](./README.md#inferencetraining-runtimes) in the `ml-model:inference-runtime` or `ml-model:training-runtime` asset roles.
41
-
- The MLM extension has a corresponding Python library, [`stac-model`](https://pypi.org/project/stac-model/) which can be used to create and validate MLM metadata. An example of the library in action is [here](https://github.com/crim-ca/mlm-extension/blob/main/stac_model/examples.py#L14). The ML Model extension does not support this and requires the JSON to be written manually by interpreting the JSON Schema or existing examples.
40
+
- The MLM Extension covers Runtime requirements within the [Container Asset](https://github.com/stac-extensions/mlm?tab=readme-ov-file#container-asset), while the ML Model Extension records [similar information](./README.md#inferencetraining-runtimes) in the `ml-model:inference-runtime` or `ml-model:training-runtime` asset roles.
41
+
- The MLM extension has a corresponding Python library, [`stac-model`](https://pypi.org/project/stac-model/) which can be used to create and validate MLM metadata. An example of the library in action is [here](https://github.com/stac-extensions/mlm/blob/main/stac_model/examples.py#L14). The ML Model extension does not support this and requires the JSON to be written manually by interpreting the JSON Schema or existing examples.
42
42
- MLM is easier to maintain and enhance in a fast moving ML ecosystem thanks to it's use of pydantic models, while still being compatible with pystac for extension and STAc core validation.
43
43
44
44
## Changes in Field Names
@@ -93,6 +93,6 @@ The MLM provides a recommended asset role for `mlm:training-runtime` and asset `
93
93
94
94
## Getting Help
95
95
96
-
If you have any questions about a migration, feel free to contact the maintainers by opening a discussion or issue on the [MLM repository](https://github.com/crim-ca/mlm-extension).
96
+
If you have any questions about a migration, feel free to contact the maintainers by opening a discussion or issue on the [MLM repository](https://github.com/stac-extensions/mlm).
97
97
98
98
If you see a feature missing in the MLM, feel free to open an issue describing your feature request.
0 commit comments