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    Models/Unconditional Image Generation/ayushshah/beta-vae-capacity-annealing-celeba

    beta-vae-capacity-annealing-celeba

    by ayushshah

    Identifier
    Model ID
    ayushshah/beta-vae-capacity-annealing-celeba

    Tags

    safetensorsvaevariational-autoencoderbeta-vaeautoencoderimage-editingdisentanglementrepresentation-learninggenerative-modelimage-generationcelebaunconditional-image-generationarxiv:1804.03599license:mitmodel-indexregion:us

    Use beta-vae-capacity-annealing-celeba on Mixpeek

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    How It Runs on Mixpeek

    On Mixpeek, beta-vae-capacity-annealing-celeba runs as a managed extractor inside a processing pipeline. Point a bucket of unconditional image generation data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.