Instructions to use dereckd/olanmills with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dereckd/olanmills with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dereckd/olanmills", dtype=torch.bfloat16, device_map="cuda") prompt = "olanmills" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2bdb503f5a835749c340030002f9de20371d6c290ecd91a15f36cb9201de6e86
- Size of remote file:
- 3.44 GB
- SHA256:
- c873003bc63e132fc688393201c867418bcfb6389c96c9b0a4bbdcfdbd40e19a
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