Instructions to use Ava2000/Mangamaster_Anima with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ava2000/Mangamaster_Anima with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ava2000/Mangamaster_Anima") prompt = "masterpiece, best quality, amazing quality, lineart, thick lines," 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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hands, extra fingers, missing fingers, extra digits, fewer digits, fused
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fingers, deformed hands, poorly drawn hands, bad anatomy, deformed
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fingers, hands with too many fingers, signature,
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- output:
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url: images/00074-1436195028.png
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text: masterpiece, best quality, amazing quality, lineart, thick lines,
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parameters:
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negative_prompt: >-
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worst quality, low quality, score_1, score_2, score_3, bad hands, mutated
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hands, extra fingers, missing fingers, extra digits, fewer digits, fused
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fingers, deformed hands, poorly drawn hands, bad anatomy, deformed
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fingers, hands with too many fingers, signature,
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base_model: oron1208/OOO_Anima
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instance_prompt: mangamaster
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# Mangamaster Style - Anima
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---
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# Mangamaster Style - Anima
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