@huggingface/tasks/src/tasks/table-question-answering/spec/input.json

List of ML tasks for huggingface.co/tasks

{
	"$id": "/inference/schemas/table-question-answering/input.json",
	"$schema": "http://json-schema.org/draft-06/schema#",
	"description": "Inputs for Table Question Answering inference",
	"title": "TableQuestionAnsweringInput",
	"type": "object",
	"properties": {
		"inputs": {
			"description": "One (table, question) pair to answer",
			"title": "TableQuestionAnsweringInputData",
			"type": "object",
			"properties": {
				"table": {
					"description": "The table to serve as context for the questions",
					"type": "object",
					"additionalProperties": {
						"type": "array",
						"items": {
							"type": "string"
						}
					}
				},
				"question": {
					"description": "The question to be answered about the table",
					"type": "string"
				}
			},
			"required": ["table", "question"]
		},
		"parameters": {
			"description": "Additional inference parameters for Table Question Answering",
			"$ref": "#/$defs/TableQuestionAnsweringParameters"
		}
	},
	"$defs": {
		"TableQuestionAnsweringParameters": {
			"title": "TableQuestionAnsweringParameters",
			"type": "object",
			"properties": {
				"padding": {
					"type": "string",
					"default": "do_not_pad",
					"description": "Activates and controls padding.",
					"enum": ["do_not_pad", "longest", "max_length"]
				},
				"sequential": {
					"type": "boolean",
					"default": "false",
					"description": "Whether to do inference sequentially or as a batch. Batching is faster, but models like SQA require the inference to be done sequentially to extract relations within sequences, given their conversational nature."
				},
				"truncation": {
					"type": "boolean",
					"default": "false",
					"description": "Activates and controls truncation."
				}
			}
		}
	},
	"required": ["inputs"]
}