Instructions to use Jephson/addsky-train-1-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jephson/addsky-train-1-0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jephson/addsky-train-1-0", 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
- Xet hash:
- 990004c6939231c451238872e891f655edc9781802a50a1a0e1bbfa930de4c6d
- Size of remote file:
- 3.44 GB
- SHA256:
- 721dfdbd7eded7e21f4115e46b7d448139821d678c2637f7b9971e9993c07d7a
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