convnext_large_mlp.clip_laion2b_soup_ft_in12k_in1k_320

Use convnext_large_mlp.clip_laion2b_soup_ft_in12k_in1k_320 on Mixpeek

Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

On Mixpeek, convnext_large_mlp.clip_laion2b_soup_ft_in12k_in1k_320 runs as a managed extractor inside a processing pipeline. Point a bucket of image classification 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.