Instructions to use warp-ai/wuerstchen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use warp-ai/wuerstchen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("warp-ai/wuerstchen", 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
File size: 438 Bytes
4b93553 04e716a 1ff6896 4b93553 1ff6896 4b93553 d255063 4b93553 26dc908 4b93553 b2b6293 4b93553 4ee74c9 4b93553 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "WuerstchenDecoderPipeline",
"_diffusers_version": "0.21.0.dev0",
"generator": [
"wuerstchen",
"WuerstchenDiffNeXt"
],
"latent_dim_scale": 10.67,
"scheduler": [
"diffusers",
"DDPMWuerstchenScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizerFast"
],
"vqgan": [
"wuerstchen",
"PaellaVQModel"
]
}
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