Instructions to use zac/anime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zac/anime with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("misri/sdxlYamersAnime_stageAnima", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("zac/anime") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("misri/sdxlYamersAnime_stageAnima", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("zac/anime")
prompt = "-"
image = pipe(prompt).images[0]anime
.png)
- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Base model
misri/sdxlYamersAnime_stageAnima