Pinecone · Schema
ModelInfo
Represents the model configuration including model type, supported parameters, and other model details.
Vector DatabasesArtificial IntelligenceEmbeddingsRAG
Properties
| Name | Type | Description |
|---|---|---|
| model | string | The name of the model. |
| short_description | string | A summary of the model. |
| type | string | The type of model (e.g. 'embed' or 'rerank'). |
| vector_type | string | Whether the embedding model produces 'dense' or 'sparse' embeddings. |
| default_dimension | integer | The default embedding model dimension (applies to dense embedding models only). |
| modality | string | The modality of the model (e.g. 'text'). |
| max_sequence_length | integer | The maximum tokens per sequence supported by the model. |
| max_batch_size | integer | The maximum batch size (number of sequences) supported by the model. |
| provider_name | string | The name of the provider of the model. |
| supported_dimensions | array | The list of supported dimensions for the model (applies to dense embedding models only). |
| supported_metrics | object | |
| supported_parameters | array | List of parameters supported by the model. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/ModelInfo",
"title": "ModelInfo",
"description": "Represents the model configuration including model type, supported parameters, and other model details.",
"type": "object",
"properties": {
"model": {
"example": "multilingual-e5-large",
"description": "The name of the model.",
"type": "string"
},
"short_description": {
"example": "multilingual-e5-large",
"description": "A summary of the model.",
"type": "string"
},
"type": {
"example": "embed",
"description": "The type of model (e.g. 'embed' or 'rerank').",
"type": "string"
},
"vector_type": {
"description": "Whether the embedding model produces 'dense' or 'sparse' embeddings.",
"type": "string"
},
"default_dimension": {
"example": 1024,
"description": "The default embedding model dimension (applies to dense embedding models only).",
"type": "integer",
"format": "int32",
"minimum": 1,
"maximum": 20000
},
"modality": {
"example": "text",
"description": "The modality of the model (e.g. 'text').",
"type": "string"
},
"max_sequence_length": {
"example": 512,
"description": "The maximum tokens per sequence supported by the model.",
"type": "integer",
"format": "int32",
"minimum": 1
},
"max_batch_size": {
"example": 96,
"description": "The maximum batch size (number of sequences) supported by the model.",
"type": "integer",
"format": "int32",
"minimum": 1
},
"provider_name": {
"example": "NVIDIA",
"description": "The name of the provider of the model.",
"type": "string"
},
"supported_dimensions": {
"description": "The list of supported dimensions for the model (applies to dense embedding models only).",
"type": "array",
"items": {
"example": 1024,
"type": "integer",
"format": "int32",
"minimum": 1,
"maximum": 20000
}
},
"supported_metrics": {
"$ref": "#/components/schemas/ModelInfoSupportedMetrics"
},
"supported_parameters": {
"description": "List of parameters supported by the model.",
"type": "array",
"items": {
"$ref": "#/components/schemas/ModelInfoSupportedParameter"
}
}
},
"required": [
"model",
"short_description",
"type",
"supported_parameters"
]
}
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