Instructions to use kraina/map_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kraina/map_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kraina/map_diffusion", 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
Download unet/diffusion_pytorch_model.bin from kraina/map_diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/kraina/map_diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://kraina/map_diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/kraina/map_diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- fddd62e7c8d1b7e47f890f54e58eadecd9e214cc25a20afebdb8e6b52d5ef7f4
- Size of remote file:
- 3.44 GB
- SHA256:
- 95c5540b0085d0329557df89c733b9d1b47e33e69b16fa2e740830e97dfc302e
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