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fix formatting errors (#116843)
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shainaraskas authored Nov 14, 2024
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Showing 1 changed file with 6 additions and 9 deletions.
15 changes: 6 additions & 9 deletions docs/reference/mapping/types/dense-vector.asciidoc
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Expand Up @@ -117,12 +117,10 @@ that sacrifices result accuracy for improved speed.
The `dense_vector` type supports quantization to reduce the memory footprint required when <<approximate-knn, searching>> `float` vectors.
The three following quantization strategies are supported:

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`int8` - Quantizes each dimension of the vector to 1-byte integers. This reduces the memory footprint by 75% (or 4x) at the cost of some accuracy.
`int4` - Quantizes each dimension of the vector to half-byte integers. This reduces the memory footprint by 87% (or 8x) at the cost of accuracy.
`bbq` - experimental:[] Better binary quantization which reduces each dimension to a single bit precision. This reduces the memory footprint by 96% (or 32x) at a larger cost of accuracy. Generally, oversampling during query time and reranking can help mitigate the accuracy loss.
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* `int8` - Quantizes each dimension of the vector to 1-byte integers. This reduces the memory footprint by 75% (or 4x) at the cost of some accuracy.
* `int4` - Quantizes each dimension of the vector to half-byte integers. This reduces the memory footprint by 87% (or 8x) at the cost of accuracy.
* `bbq` - experimental:[] Better binary quantization which reduces each dimension to a single bit precision. This reduces the memory footprint by 96% (or 32x) at a larger cost of accuracy. Generally, oversampling during query time and reranking can help mitigate the accuracy loss.


When using a quantized format, you may want to oversample and rescore the results to improve accuracy. See <<dense-vector-knn-search-reranking, oversampling and rescoring>> for more information.

Expand Down Expand Up @@ -245,12 +243,11 @@ their vector field's similarity to the query vector. The `_score` of each
document will be derived from the similarity, in a way that ensures scores are
positive and that a larger score corresponds to a higher ranking.
Defaults to `l2_norm` when `element_type: bit` otherwise defaults to `cosine`.

NOTE: `bit` vectors only support `l2_norm` as their similarity metric.

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^*^ This parameter can only be specified when `index` is `true`.
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NOTE: `bit` vectors only support `l2_norm` as their similarity metric.

.Valid values for `similarity`
[%collapsible%open]
====
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