Instructions to use d-wang26/wd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use d-wang26/wd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("d-wang26/wd", 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
Download diffusers/_typos.toml from d-wang26/wd: direct link, hf CLI and curl.
- Browser
- Download file 407 Bytes
-
https://huggingface.co/d-wang26/wd/resolve/main/diffusers/_typos.toml
- Command line
-
hf download hf://d-wang26/wd/diffusers/_typos.toml
-
curl -L -o _typos.toml https://huggingface.co/d-wang26/wd/resolve/main/diffusers/_typos.toml
407 Bytes
| # Files for typos | |
| # Instruction: https://github.com/marketplace/actions/typos-action#getting-started | |
| [default.extend-identifiers] | |
| [default.extend-words] | |
| NIN="NIN" # NIN is used in scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py | |
| nd="np" # nd may be np (numpy) | |
| parms="parms" # parms is used in scripts/convert_original_stable_diffusion_to_diffusers.py | |
| [files] | |
| extend-exclude = ["_typos.toml"] | |