Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
food
Instructions to use kokuma/mazapan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kokuma/mazapan with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kokuma/mazapan", dtype=torch.bfloat16, device_map="cuda") prompt = "a cute bunny, mazapan" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from kokuma/mazapan: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/kokuma/mazapan/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://kokuma/mazapan/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/kokuma/mazapan/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 475785fdc9f216675c26221c62892c0e0d03a53c3e205678a5f38ce12fed8eaf
- Size of remote file:
- 335 MB
- SHA256:
- dcf4507d99b88db73f3916e2a20169fe74ada6b5582e9af56cfa80f5f3141765
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