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
- Draw Things
- DiffusionBee
- Xet hash:
- bbb239061a29ea176fd0ee1faf676fb6aaac4475977583080297e75a50bc1285
- Size of remote file:
- 335 MB
- SHA256:
- a403938a533901a19513a61191bd164cd58bb99121db24cb8175405f7773f7b7
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