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
- __pycache__
- advanced_diffusion_training
- amused
- community
- consistency_distillation
- controlnet
- custom_diffusion
- dreambooth
- inference
- instruct_pix2pix
- kandinsky2_2
- reinforcement_learning
- research_projects
- t2i_adapter
- text_to_image
- textual_inversion
- unconditional_image_generation
- wuerstchen
- 6.55 kB
- 1.72 kB
- 2.05 kB