Instructions to use SeanZheng/Distill-WAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SeanZheng/Distill-WAM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SeanZheng/Distill-WAM", 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
galaxea-a1-nyush-relation-left-flashwam-step24: weights
Browse files
galaxea-a1-nyush-relation-left-flashwam-step24/transformer/diffusion_pytorch_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:99cbf88f536ba45b9bc00f62162ee7c623300a76b1cce1070ccb15095aa0490f
|
| 3 |
+
size 19997351340
|