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
Delete unet
Browse files- unet/unet.ckpt +0 -3
unet/unet.ckpt
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:130d012a6efd1aa24e5e1c03eb9948262e53ec1ccbae04f4e5c489743d66d8dc
|
| 3 |
-
size 198762352
|
|
|
|
|
|
|
|
|
|
|
|