Instructions to use recoilme/transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/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("recoilme/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:
- 964289ea5d461b998dcdb72f8cb3199b602ec3e1020f48baaa050f6d9221076c
- Size of remote file:
- 3.91 GB
- SHA256:
- 2dd60633bdfa58b241b70de6aae5f345a6ae08ccfa18fd04685d3de0b1c1caf5
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