Instructions to use Tinsae/atc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tinsae/atc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tinsae/atc", 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:
- 399f057fb1a1897b3a0d03505d923d09c0de84d3b3370cd2668487fa3149c94d
- Size of remote file:
- 2.13 GB
- SHA256:
- 19fad2b38e283fd6e4c38412e692bf0b9e6453d83c0cfa00419a19d0333693a3
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