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:
- 161dedf15a56c7e40c0f53e7ff98fbb126a635e253a6da0af95925391b2c34a2
- Size of remote file:
- 2.41 GB
- SHA256:
- 9d7bcf85b4ed43a187a644369fba99d63ac40ac8738a1b3cd17cf4ea9aa3a5fe
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