Model reference · open weights

japanese-avhubert-large_noise_pt

Embeddings enactic Embeddings 1 build Non-commercial 509 dl/mo

japanese-avhubert-large_noise_pt is an open-weight embedding model from enactic. japanese-avhubert-large_noise_pt (FP32) weighs 649 MB; the smallest configuration that runs it is RTX 3060 12 GB.

  • japanese-avhubert-large_noise_pt is a 325M parameter feature-extraction model developed by enactic for audio-visual speech recognition.
  • It is a self-supervised AVHuBERT variant pretrained on approximately 2,250 hours of Japanese data with noise augmentation to handle noisy environments.
  • The model supports Japanese and is released under the cc-by-nc-4.0 license.

Summary of the enactic/japanese-avhubert-large_noise_pt model card, 2026-10-01

What it is

Released byenactic
Released2026-01-14
Parameters325M
VRAM649 MB for the weights

What it runs on

Memory and cards for japanese-avhubert-large_noise_pt (FP32)

649 MBweights, file size
1.1 GBruntime overhead
CardRunsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together, which is the basis of search and RAG.
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