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:
- 2fd33c69525f1d9ed0cba274c168d54445f83dcbd6f4eeb2e8999966c608fa68
- Size of remote file:
- 335 MB
- SHA256:
- ed69dc392cd50e365844a708921abe7ae490ff7a73bfb0e46add644c3b614de6
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