Instructions to use Hishambarakat/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hishambarakat/checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hishambarakat/checkpoint", 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
- Local Apps
- Draw Things
- DiffusionBee
Upload /pony/ponyDiffusionV6XL_v6StartWithThisOne.safetensors with huggingface_hub
Browse files
pony/ponyDiffusionV6XL_v6StartWithThisOne.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:67ab2fd8ec439a89b3fedb15cc65f54336af163c7eb5e4f2acc98f090a29b0b3
|
| 3 |
+
size 6938041050
|