Instructions to use 8BitStudio/Aniimage-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 8BitStudio/Aniimage-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("8BitStudio/Aniimage-2", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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@@ -38,4 +38,24 @@ It is not based on any existing models, the UNet is trained from scratch.
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- **GPU**: ~6 GB VRAM minimum (recommend 8+ GB)
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- **CPU**: ~7 GB RAM. Image generation is extremely slow on CPU. (recommend 10+ GB)
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- **GPU**: ~6 GB VRAM minimum (recommend 8+ GB)
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- **CPU**: ~7 GB RAM. Image generation is extremely slow on CPU. (recommend 10+ GB)
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## Prompting
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Aniimage uses plain text captions as well as Danbooru tags.
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An example of acceptable captions:
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"A smiling anime girl with red hair and a school uniform"
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"1girl, solo, smile, red_hair, school_uniform, anime_coloring"
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Long prompts and enhanced prompts usually result in worse overall results. Try to keep your prompts short.
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Adding a negative prompt is required for a good output. The one used during inference in the preview image is
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"low quality, ugly, blurry, distorted, deformed, bad anatomy, bad proportions, extra limbs, missing limbs, watermark,
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text, signature, washed out, flat colors, manga panel, disfigured, poorly drawn, jpeg artifacts, cropped, out of frame"
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for the best quality, use DPM++ SDE at 50 steps.
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**important** If you do not put 'NSFW' in the negative prompt, it will most likely make nsfw images.
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