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v1.14: New pooling parameter for Hugging Face embedders #3212

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Merged
Parent: v1.14
merged 5 commits into from
Apr 9, 2025
Merged

v1.14: New pooling parameter for Hugging Face embedders #3212

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c25b644
add pooling parameter to embedder settings
guimachiavelli Apr 1, 2025
b920018
escape `<` for better mdx syntax highlighting
guimachiavelli Apr 1, 2025
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shorten explanation text
guimachiavelli Apr 1, 2025
2efe272
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guimachiavelli Apr 3, 2025
9cfa5f1
Merge branch 'v1.14' into 3189-v1.14-pooling-parameter
guimachiavelli Apr 9, 2025
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22 changes: 20 additions & 2 deletions reference/api/settings.mdx
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Expand Up @@ -2435,10 +2435,11 @@ These embedder objects may contain the following fields:
| **`revision`** | String | Empty | Model revision hash |
| **`distribution`** | Object | Empty | Describes the natural distribution of search results. Must contain two fields, `mean` and `sigma`, each containing a numeric value between `0` and `1` |
| **`request`** | Object | Empty | A JSON value representing the request Meilisearch makes to the remote embedder |
| **`response`** | Object | Empty | A JSON value representing the request Meilisearch expects from the remote embedder |
| **`response`** | Object | Empty | A JSON value representing the response Meilisearch expects from the remote embedder |
| **`binaryQuantized`** | Boolean | Empty | Once set to `true`, irreversibly converts all vector dimensions to 1-bit values |
| **`indexingEmbedder`** | Object | Empty | Configures embedder to vectorize documents during indexing |
| **`searchEmbedder`** | Object | Empty | Configures embedder to vectorize search queries |
| **`pooling`** | String | `"useModel"` | Pooling method for Hugging Face embedders |

### Get embedder settings

Expand All @@ -2450,7 +2451,7 @@ Get the embedders configured for an index.

| Name | Type | Description |
| :---------------- | :----- | :------------------------------------------------------------------------ |
| **`index_uid`** * | String | [`uid`](/learn/getting_started/indexes#index-uid) of the requested index |
| **`index_uid`** * | String | [`uid`](/learn/getting_started/indexes#index-uid) of the requested index |

#### Example

Expand Down Expand Up @@ -2503,6 +2504,7 @@ Partially update the embedder settings for an index. When this setting is update
"response": { … },
"headers": { … },
"binaryQuantized": <Boolean>,
"pooling": <String>,
"indexingEmbedder": { … },
"searchEmbedder": { … }
}
Expand Down Expand Up @@ -2762,6 +2764,22 @@ This option can be useful when working with large Meilisearch projects. Consider
**Activating `binaryQuantized` is irreversible.** Once enabled, Meilisearch converts all vectors and discards all vector data that does fit within 1-bit. The only way to recover the vectors' original values is to re-vectorize the whole index in a new embedder.
</Capsule>

##### `pooling`

Configure how Meilisearch should merge individual tokens into a single embedding.

`pooling` must be one of the following strings:

- `"useModel"`: Meilisearch will fetch the pooling method from the model configuration. Default value for new embedders
- `"forceMean"`: always use mean pooling. Default value for embedders created in Meilisearch \<=v1.13
- `"forceCls"`: always use CLS pooling

If in doubt, use `"useModel"`. `"forceMean"` and `"forceCls"` are compatibility options that might be necessary for certain embedders and models.

`pooling` is optional for embedders with the `huggingFace` source.

`pooling` is invalid for all other embedder sources.

##### `indexingEmbedder` and `searchEmbedder` <NoticeTag type="experimental" label="experimental" />

When using a [composite embedder](#composite-embedders), configure separate embedders Meilisearch should use when vectorizing documents and search queries.
Expand Down