Contributing to task page for any-to-any

packages/tasks/src/tasks/any-to-any/about.md

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+## Use Cases
+
+You can contribute this area with common use cases of the task!
+
+## Task Variants
+
+This place can be filled with variants of this task if there's any.
+
+## Inference
+
+This section should have useful information about how to pull a model from Hugging Face Hub that is a part of a library specialized in a task and use it.
+
+## Useful Resources
+
+In this area, you can insert useful resources about how to train or use a model for this task.

packages/tasks/src/tasks/any-to-any/data.ts

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+import type { TaskDataCustom } from "..";
+
+const taskData: TaskDataCustom = {
+	datasets: [{
+			description:  "All-Modality Alignment Dataset with Fine-grained Preference Annotations and Language Feedback.",
+			id: "PKU-Alignment/align-anything-400k",
+		},],
+	demo: {
+		inputs: [],
+		outputs: [],
+	},
+	metrics: [],
+	models: [
+		{
+			description: "A next token prediction model.",
+			id: "BAAI/Emu3-Gen",
+		},
+		{
+			description: "Janus is a versatile multimodal framework that decouples visual encoding for superior understanding and generation across tasks.",
+			id: "deepseek-ai/Janus-1.3B",
+		},
+	],	spaces: [
+		{
+			description: "Janus is a versatile multimodal framework that decouples visual encoding for superior understanding and generation across tasks.",
+			id: "deepseek-ai/Janus-1.3B",
+		},
+	],
+	summary: "Any-to-Any can leverage any combination of input and output types to such as text, image, and video. It  may combine other datasets to train a comprehensive LLM.",
+	widgetModels: [],
+	youtubeId: "",
+};
+
+export default taskData;