Instructions to use ShinnosukeU/parameter_v14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShinnosukeU/parameter_v14 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShinnosukeU/parameter_v14", 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 ShinnosukeU/parameter_v14: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/ShinnosukeU/parameter_v14/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ShinnosukeU/parameter_v14/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ShinnosukeU/parameter_v14/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 96493d36b67e81e152c3fd883bf31423498f76c0c3aa78f9f29495420947df3b
- Size of remote file:
- 3.44 GB
- SHA256:
- a5cc427b04a06f4c75e80bd91de4a895cd4f40458717ca76bd663687a294647e
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