Instructions to use animEEEmpire/AniMemory-alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use animEEEmpire/AniMemory-alpha with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("animEEEmpire/AniMemory-alpha", 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
devancao commited on
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Parent(s): 73833a8
readme update
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README.md
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@@ -21,6 +21,7 @@ of the anime community, and we greatly value any feedback.
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through our workflow.
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- Better support for Chinese-style elements.
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- Compatible with both tag lists and natural language description-style prompts.
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# Model Info
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through our workflow.
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- Better support for Chinese-style elements.
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- Compatible with both tag lists and natural language description-style prompts.
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- Centered on a resolution of 1024, e.g. 896 * 1152 for vertical image output.
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# Model Info
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