Instructions to use lunachan/wd15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lunachan/wd15 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lunachan/wd15", 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 text_encoder/pytorch_model.bin from lunachan/wd15: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/lunachan/wd15/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://lunachan/wd15/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lunachan/wd15/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- c19bf7538f9609802438b7f00519bb28a1810ea07d085c4d8f22e86b774c4a89
- Size of remote file:
- 1.36 GB
- SHA256:
- 545bc8a2d5ca571a6124897a261b0705e926c84cc1b17e61b1de7f01c62866fd
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