Instructions to use alc15492/emjs30_30_3000steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alc15492/emjs30_30_3000steps with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alc15492/emjs30_30_3000steps", 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:
- 9f29e296334e6e536973ec05cd1e0b21d2aad45db5d5548ffe92bc0fa531a2ad
- Size of remote file:
- 6.59 MB
- SHA256:
- f4f6c19c2f781f1c192f3dd99969a927dde9419a2a44b3d024c7b249b750380b
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