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Bird's/Worm's eye view(Extreme from above/from below)

Name: Bird's/Worm's eye view(Extreme from above/from below)
Rating: 5 (49 reviews)
Author: wraith_executioner_year_2

282

Updated: Jul 7, 2026

concept

bird's eye view worm's eye view

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bf16 SafeTensor

concept_eye_view_v0.0.0-000010.safetensors

BF16, good balance • 33.27 MB

Verified: 2 days ago

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Details

Type

LoRA

Stats

282

Reviews

Positive

(49)

Published

Jul 7, 2026

Base Model

Anima

Hash

AutoV2

34F74C96CA

Trigger Words

bird's eye view

from above

worm's eye view

from below

wide shot

very wide shot

perspective

fisheye

vanishing point

Tensors

About this version

Initial.

Known Issues: When using the trigger words bird's eye view or worm's eye view, the model may accidentally generate literal "eyes" or "worm-like monsters" in the image due to word associations.

To bypass this, please use from above / from below instead, or use the negative prompt to filter out and remove those unwanted artifacts.

Used settings:

dim8/alpha8, unet 1e-05(adamw8bit/cosine_with_restarts[2]), 100images / 1000 steps

Extra network args:

block_dims=0,0,0,0,4,4,8,8,8,8,8,4,4,0,0,0,0 block_alphas=8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8 conv_dim=0 conv_alpha=1 rank_dropout=0.25 module_dropout=0.1

default creator card background decoration

155

1.1K

wraith_executioner_year_2

Joined Jun 6, 2025

License:

Anima

The Anima Model is licensed by CircleStone Labs LLC. Copyright CircleStone Labs LLC. IN NO EVENT SHALL CIRCLESTONE LABS LLC BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

Built on NVIDIA Cosmos

The camera angles in the training dataset are oriented either perfectly aligned with gravity or pointing directly in the opposite direction.

I captioned the perfectly top-down images as bird's eye view and the perfectly bottom-up images as worm's eye view, then trained the model on anima_baseV10.

Tip for FT Models: When using this LoRA with already fine-tuned (FT) models, you can achieve the same intense effect by heavily boosting the weights of the standard tags, such as using (from_above:3) or (from_below:3).