Instructions to use Anzhc/AAAAnima with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Anzhc/AAAAnima with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Anzhc/AAAAnima", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -39,12 +39,12 @@ dpm++ sde, 16-24 steps, cfg 3.5-7, shift 4
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## How was it trained
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Lr: variable LR per block group, from 3e-6 to 5e-6, from early to late.
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Adapter: frozen.
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Loss: L2, with some modifications for rare aspect ratio buckets and depth.
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Schedule: Logit-Normal -0.2 1.5(or was it 1.5 -0.2...)(Bluvoll's schedule) with shift 4 and normal tail sampling modification. (Tldr, all that fixes lack of front in default logit normal and normalizes amount of sampling at the very late timesteps, without making them overbearing at high shift.)
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Captions: tags only. (you won't make me suffer through captioning 12k images with gemma 4 31b or qwen 3.6 27b locally for NL counterpart)
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## Examples
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Anima base 1.0 on left, this fintune on right.
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## How was it trained
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+
Lr: variable LR per block group, from 3e-6 to 5e-6, from early to late.
|
| 43 |
+
Adapter: frozen.
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| 44 |
+
Loss: L2, with some modifications for rare aspect ratio buckets and depth.
|
| 45 |
+
Schedule: Logit-Normal -0.2 1.5(or was it 1.5 -0.2...)(Bluvoll's schedule) with shift 4 and normal tail sampling modification. (Tldr, all that fixes lack of front in default logit normal and normalizes amount of sampling at the very late timesteps, without making them overbearing at high shift.)
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| 47 |
+
Captions: tags only. (you won't make me suffer through captioning 12k images with gemma 4 31b or qwen 3.6 27b locally for NL counterpart)
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| 48 |
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## Examples
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| 50 |
Anima base 1.0 on left, this fintune on right.
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