AniGen Sample Data: A 10-Example Multimodal Subset for Generative AI

VAST-AI provides a compact 10-example subset of the AniGen training dataset for generative AI. This sample includes unique raw assets and full cross-modal files across multiple directories like raw, renders, skeleton, and voxels. The dataset was last updated on April 13, 2026.

Use Cases

• Testing multimodal model pipelines based on the provided raw assets and renders.
• Benchmarking auto-encoder performance using the included latent and ss_latent directories.
• Analyzing cross-modal data alignment based on the full set of files for each example.

Strengths

• Contains 10 unique examples with full cross-modal files for each.
• Retains the core directory structure of the reference test set, including 7 distinct data types.

Limitations

• The sample size of 10 rows may not be representative for model training.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the full dataset is unknown, which may limit suitability assessment.

Provenance

Source

VAST-AI

Collection Method

Likely a curated subset extracted from a larger generative AI training dataset.

Time Range

null

Freshness

Last updated 2026-04-13 11:53:33.

Geography

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