Instructions to use jayparmr/model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jayparmr/model1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jayparmr/model1", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 53a0e09c658f263fa835ab1bcef33f4e89683c95d1434382c5aea08cb664f9a2
- Size of remote file:
- 335 MB
- SHA256:
- 8ce9f3bb3c79580531f8b0c6c7cff7b7332e54a516094d49e5a2df6088d10c9b
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