@huggingface/tasks/src/tasks/feature-extraction/spec/input.json

List of ML tasks for huggingface.co/tasks

{
	"$id": "/inference/schemas/feature-extraction/input.json",
	"$schema": "http://json-schema.org/draft-06/schema#",
	"description": "Feature Extraction Input.\n\nAuto-generated from TEI specs.\nFor more details, check out https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-tei-import.ts.",
	"title": "FeatureExtractionInput",
	"type": "object",
	"required": ["inputs"],
	"properties": {
		"inputs": {
			"title": "FeatureExtractionInputs",
			"description": "The text or list of texts to embed.",
			"oneOf": [
				{
					"type": "string"
				},
				{
					"type": "array",
					"items": {
						"type": "string"
					}
				}
			]
		},
		"normalize": {
			"type": "boolean",
			"default": "true",
			"example": "true"
		},
		"prompt_name": {
			"type": "string",
			"description": "The name of the prompt that should be used by for encoding. If not set, no prompt\nwill be applied.\n\nMust be a key in the `sentence-transformers` configuration `prompts` dictionary.\n\nFor example if ``prompt_name`` is \"query\" and the ``prompts`` is {\"query\": \"query: \", ...},\nthen the sentence \"What is the capital of France?\" will be encoded as\n\"query: What is the capital of France?\" because the prompt text will be prepended before\nany text to encode.",
			"default": "null",
			"example": "null",
			"nullable": true
		},
		"truncate": {
			"type": "boolean",
			"default": "false",
			"example": "false",
			"nullable": true
		},
		"truncation_direction": {
			"allOf": [
				{
					"$ref": "#/$defs/FeatureExtractionInputTruncationDirection"
				}
			],
			"default": "right"
		}
	},
	"$defs": {
		"FeatureExtractionInputTruncationDirection": {
			"type": "string",
			"enum": ["left", "right"],
			"title": "FeatureExtractionInputTruncationDirection"
		}
	}
}