Instructions to use hf-internal-testing/tiny-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-adapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-adapter", 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:
- 7fb225e1f0a11f0d1963045cb48c1ea3dbb15259b2009cf532d08e2fd3cdda24
- Size of remote file:
- 477 kB
- SHA256:
- 00a69332b115ce43c47c2f7d0fce4a94dbd57dc557e09600cf50c2cc5756966d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.