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 checkpoint-6500/optimizer.bin from d-wang26/wd: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/d-wang26/wd/resolve/main/checkpoint-6500/optimizer.bin
- Command line
-
hf download hf://d-wang26/wd/checkpoint-6500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/d-wang26/wd/resolve/main/checkpoint-6500/optimizer.bin
910 MB
- Xet hash:
- 392071f28133e336cac108b894b2a9bbd4182ea210ececf2a1c26b3c1e9514d5
- Size of remote file:
- 910 MB
- SHA256:
- 94270806a852a1f9ee6ba44d58a24b87e0b84d23e872232195ac09aa2aa3fdc7
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