Instructions to use snow-leopard/init_baseline_test_transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use snow-leopard/init_baseline_test_transformer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("snow-leopard/init_baseline_test_transformer", torch_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:
- e059d75ad5ef482cdeeba846f1db835104005dd8e179ec14298dcf5a0fba2abb
- Size of remote file:
- 2.41 GB
- SHA256:
- 86eb266f10ccfae17171c9f64bcb0716627a0d0ea2b5fd6abeec9e23d6fb9448
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