Instructions to use Tinsae/doorstop1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tinsae/doorstop1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tinsae/doorstop1", 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:
- c47aefe90374e990253ed6c9702e5a9c4193ea7185e22d8b8d9233435ff18fcd
- Size of remote file:
- 246 MB
- SHA256:
- 3f34f5c6d10968f43a02bc2131ffb01b60282d45bb5dfbb37d421ad50fbf2bb5
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