Instructions to use dhanushkaha/diffusion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dhanushkaha/diffusion_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dhanushkaha/diffusion_model", torch_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
- Xet hash:
- 279e759f154c4cc8384d0a3e6a5a8011c10d5ba21b3634e5d36f2ecddfe19031
- Size of remote file:
- 492 MB
- SHA256:
- d1555094dacaff5c8dd8998c6a16f4ebf60e1c41c845e68b9e249e474e840a29
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