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Identifier
Model ID
BUT-FIT/diarizen-wavlm-large-s80-md-v2Tags
transformerspytorchspeakerspeaker-diarizationmeetingwavlmwespeakerdiarizenpyannotepyannote-audio-pipelinevoice-activity-detectionarxiv:2505.24111arxiv:2506.18623license:cc-by-nc-4.0endpoints_compatibleregion:us
Use diarizen-wavlm-large-s80-md-v2 on Mixpeek
Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.
Open StudioHow It Runs on Mixpeek
On Mixpeek, diarizen-wavlm-large-s80-md-v2 runs as a managed extractor inside a processing pipeline. Point a bucket of voice activity detection 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.
Specification
OrganizationBUT-FIT
TaskVoice Activity Detection
Librarytransformers
Licensecc-by-nc-4.0
Downloads/mo2K
Likes17
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