edge-fall-vlm-256m — 256M fall / danger detector (size-comparison sibling)
A SmolVLM2-256M-Video-Instruct fine-tune for fall / person-down / distress detection, same recipe as
edge-fall-vlm-2.2b but at 256M.
Published mainly to show how accuracy scales with VLM size.
Accuracy vs size (same recipe, same real test sets)
Model
URFD (easy) recall/spec
OOPS in-the-wild recall
256M
1.0 / 1.0
0.13
500M
1.0 / 1.0
0.31
2.2B (recommended)
0.90 / 1.0
0.83
This 256M model saturates the easy in-distribution test but MISSES most real in-the-wild
falls (recall 0.13). Smaller VLMs fit the training distribution but do not generalize to
novel real footage. For the actual safety task, use the 2.2B. This model is useful for
research / the fastest possible on-device path where recall is not safety-critical.
Files: transformers model.safetensors + model-Q8_0.gguf / mmproj-f16.gguf
(llama.cpp). Apache-2.0. Not a medical/safety device.
