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
File size: 505 Bytes
61465c1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"_class_name": "FlowMatchEulerDiscreteScheduler",
"_diffusers_version": "0.37.0.dev0",
"base_image_seq_len": 256,
"base_shift": 0.5,
"invert_sigmas": false,
"max_image_seq_len": 4096,
"max_shift": 1.15,
"num_train_timesteps": 1000,
"shift": 6.0,
"shift_terminal": null,
"stochastic_sampling": false,
"time_shift_type": "exponential",
"use_beta_sigmas": false,
"use_dynamic_shifting": false,
"use_exponential_sigmas": false,
"use_karras_sigmas": false
}
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