Instructions to use mcuo/Anime-Z with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mcuo/Anime-Z with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mcuo/Anime-Z", 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
- Draw Things
- DiffusionBee
Upload config.json
Browse files- config.json +1 -1
config.json
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"diffusers_folder": {
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"path": "diffusers/",
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"pipeline_class": "ZImagePipeline",
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"usage": "ZImagePipeline.from_pretrained('mcuo/Anime-
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"components": [
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"model_index.json",
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"scheduler/",
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"diffusers_folder": {
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"path": "diffusers/",
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"pipeline_class": "ZImagePipeline",
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"usage": "ZImagePipeline.from_pretrained('mcuo/Anime-Z', subfolder='diffusers', torch_dtype=torch.bfloat16)",
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"components": [
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"model_index.json",
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"scheduler/",
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