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/examples/controlnet/requirements_flax.txt from d-wang26/wd: direct link, hf CLI and curl.
- Browser
- Download file 83 Bytes
-
https://huggingface.co/d-wang26/wd/resolve/main/diffusers/examples/controlnet/requirements_flax.txt
- Command line
-
hf download hf://d-wang26/wd/diffusers/examples/controlnet/requirements_flax.txt
-
curl -L -o requirements_flax.txt https://huggingface.co/d-wang26/wd/resolve/main/diffusers/examples/controlnet/requirements_flax.txt
83 Bytes
| transformers>=4.25.1 | |
| datasets | |
| flax | |
| optax | |
| torch | |
| torchvision | |
| ftfy | |
| tensorboard | |
| Jinja2 | |