Merge branch 'main' into add-link-to-local-chat

Author: DePasqualeOrg

packages/tasks/package.json

@@ -1,7 +1,7 @@
 {
 	"name": "@huggingface/tasks",
 	"packageManager": "[email protected]",
-	"version": "0.13.8",
+	"version": "0.13.9",
 	"description": "List of ML tasks for huggingface.co/tasks",
 	"repository": "https://github.com/huggingface/huggingface.js.git",
 	"publishConfig": {

packages/tasks/src/tasks/table-question-answering/inference.ts

@@ -14,9 +14,7 @@ export interface TableQuestionAnsweringInput {
 	/**
 	 * Additional inference parameters for Table Question Answering
 	 */
-	parameters?: {
-		[key: string]: unknown;
-	};
+	parameters?: TableQuestionAnsweringParameters;
 	[property: string]: unknown;
 }
 /**
@@ -35,6 +33,30 @@ export interface TableQuestionAnsweringInputData {
 	};
 	[property: string]: unknown;
 }
+/**
+ * Additional inference parameters for Table Question Answering
+ */
+export interface TableQuestionAnsweringParameters {
+	/**
+	 * Activates and controls padding.
+	 */
+	padding?: Padding;
+	/**
+	 * 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.
+	 */
+	sequential?: boolean;
+	/**
+	 * Activates and controls truncation.
+	 */
+	truncation?: boolean;
+	[property: string]: unknown;
+}
+/**
+ * Activates and controls padding.
+ */
+export type Padding = "do_not_pad" | "longest" | "max_length";
 export type TableQuestionAnsweringOutput = TableQuestionAnsweringOutputElement[];
 /**
  * Outputs of inference for the Table Question Answering task

packages/tasks/src/tasks/table-question-answering/spec/input.json

@@ -36,7 +36,24 @@
 		"TableQuestionAnsweringParameters": {
 			"title": "TableQuestionAnsweringParameters",
 			"type": "object",
-			"properties": {}
+			"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"]