Qdrant · Schema
QuantizationSearchParams
Additional parameters of the search
Artificial IntelligenceVector Databases
Properties
| Name | Type | Description |
|---|---|---|
| ignore | boolean | If true, quantized vectors are ignored. Default is false. |
| rescore | boolean | If true, use original vectors to re-score top-k results. Might require more time in case if original vectors are stored on disk. If not set, qdrant decides automatically apply rescoring or not. |
| oversampling | number | Oversampling factor for quantization. Default is 1.0. Defines how many extra vectors should be preselected using quantized index, and then re-scored using original vectors. For example, if `oversampli |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/QuantizationSearchParams",
"title": "QuantizationSearchParams",
"description": "Additional parameters of the search",
"type": "object",
"properties": {
"ignore": {
"description": "If true, quantized vectors are ignored. Default is false.",
"default": false,
"type": "boolean"
},
"rescore": {
"description": "If true, use original vectors to re-score top-k results. Might require more time in case if original vectors are stored on disk. If not set, qdrant decides automatically apply rescoring or not.",
"type": "boolean",
"nullable": true
},
"oversampling": {
"description": "Oversampling factor for quantization. Default is 1.0.\n\nDefines how many extra vectors should be preselected using quantized index, and then re-scored using original vectors.\n\nFor example, if `oversampling` is 2.4 and `limit` is 100, then 240 vectors will be preselected using quantized index, and then top-100 will be returned after re-scoring.",
"type": "number",
"format": "double",
"minimum": 1,
"nullable": true
}
}
}
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