Instructions to use almost/athing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use almost/athing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("almost/athing", 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:
- 2cde46d306da9ef6eba32b844677c344466033a20a3a86628bfa87f3ffd187ce
- Size of remote file:
- 492 MB
- SHA256:
- a75f03bb72ccb031c2b7cfd963f6a9088008fded48c06cc8294748147444cb04
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