Skip to content

Add lasttoken and none pooling modes to text embedding model docs #12390

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
aneesh-db wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Add lasttoken and none pooling modes to text embedding model docs #12390

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion _ml-commons-plugin/api/model-apis/register-model.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,7 @@ You can further customize a pretrained sentence transformer model's post-process

| Field | Data type | Description |
| :--- | :--- | :--- |
| `pooling_mode` | String | The post-process model output, either `mean`, `mean_sqrt_len`, `max`, `weightedmean`, or `cls`.|
| `pooling_mode` | String | The post-process model output, either `mean`, `mean_sqrt_len`, `max`, `weightedmean`, `cls`, `lasttoken`, or `none`. Use `lasttoken` for decoder-only models (for example, Qwen3-Embedding) where the final non-padding token captures cumulative context through causal attention. Use `none` for models that already provide pre-pooled output (such as `sentence_embedding` or `pooler_output`) to skip additional pooling.|
| `normalize_result` | Boolean | When set to `true`, normalizes the model output in order to scale to a standard range for the model. |

## Example request: Custom model
Expand Down
Loading