Instructions to use hf-internal-testing/tiny-lumina2-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-lumina2-pipe 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-lumina2-pipe", 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:
- fd51c90507779e48ec6663538efc4e967d98ff2cd94e03f56426413e352cce3b
- Size of remote file:
- 8.2 MB
- SHA256:
- 0ddf0a51ec79c1dbee9b0219481950009540be33b23d6e5b52754eb21c9c36a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.