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", 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:
- 99194065471a8cfb7d892c4eb3f628fa2b19cc7d78498f846dcba9f7a9fe3d82
- Size of remote file:
- 2.41 GB
- SHA256:
- b2eb3f2c5671b870f5980072096935ffa3e9f33cc91d4e38e3f79500c7f331f7
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