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chibifire/anny-camera-lora
anny-camera-lora is a machine learning model from chibifire. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
A camera-control LoRA for OmniGen2, trained on chibifire/anny-render-corpus.
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.safetensors20.5 MB · 100%
From the Hugging Face model README
A camera-control LoRA for OmniGen2, trained on
chibifire/anny-render-corpus.
Code: weftspun/anny-render-corpus, on the 6-datasource side of the hexagon.
Identical prompts, identical seed, only the weights differ. Azimuth is recovered by fitting the ANNY body to detected keypoints, so it is arithmetic on the body rather than an opinion about the picture.
| requested | base model | with this adapter |
|---|---|---|
| 0 | 10.4 off | 6.2 off |
| 90 | 97.6 off | 13.3 off |
| 180 | 11.9 off | 18.6 off |
| 45, 135 | wrong | no person detected |
| 225, 270, 315 | wrong | still wrong |
Slope of recovered against requested: 0.04 to 0.10.
This adapter is undertrained and this card says so. It learned the three cardinal directions and overfit elsewhere, which is what 95 images of one body should produce. It does not yet deliver general camera control, and the slope is the number to watch.
200 steps, 22 minutes, one RTX 3090. Rank 8, alpha 8, attention only
(to_k, to_q, to_v, to_out.0), bf16, gradient checkpointing, 8-bit AdamW, batch 1 with
8 accumulation steps, 256 square. Loss 0.196 to 0.111.
512 square did not complete a step in twelve minutes on the same card, and raised nothing: the driver pages into shared memory rather than failing.
adapter_model.safetensors carries the 304 trained tensors, 19.52 MiB. The trainer's own
checkpoint is 14.8 GiB because it saves the whole model under FSDP, and 866 of those tensors
are the base model unchanged.
Load this against OmniGen2/OmniGen2 at revision
df5dca8a981d74e6c3af214c145f5c735fe72367. That exact revision is also mirrored at
chibifire/omnigen2-base-df5dca8a,
unmodified and Apache-2.0, so a cited revision stays fetchable if upstream moves. Use upstream
when you can; the mirror is the fallback.
An adapter is deltas against a base it cannot function without, so the pair is only useful together.