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patrickamadeus/
dt-kvbridge-nogate-image-1800

Name: dt-kvbridge-nogate-image-1800
Availability: InStock

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PrefixVLM

PrefixVLM is a dual-language-model vision-language architecture with one-pass K/V transport:

Left LM (left_lm) builds image-conditioned memory.
Right LM (right_lm) performs continuation.
Optional K/V bridge transforms left K/V before transport.
transport_mode supports image (visual-token transport) and full (full-sequence transport).
Optional gate (use_gate=True) applies feature-wise modulation: sigmoid(Wx) (no bias).

Load

python

from models.prefix_vlm import PrefixVLM
model = PrefixVLM.from_pretrained("patrickamadeus/dt-kvbridge-nogate-image-1800")

Build from backbone configs

python

from models.config import VLMConfig
from models.prefix_vlm import PrefixVLM

cfg = VLMConfig()
model = PrefixVLM(cfg=cfg, load_backbone=True, bridge_mode="linear", bridge_use_gate=True)