Instructions to use numinllar/work_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use numinllar/work_dir with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("numinllar/work_dir", 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:
- 21385d450ab5a76f220c276bcb122de83234de63e646e7bf3d10ec4e34c9e2af
- Size of remote file:
- 6.1 GB
- SHA256:
- 0379600297ad8840bc84d35c4d911d1e708b519e84ee6a5a0e570365ee64a5a9
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