Instructions to use JunhaoZhuang/Cobra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JunhaoZhuang/Cobra with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JunhaoZhuang/Cobra", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add library_name to metadata
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,11 +1,13 @@
|
|
| 1 |
---
|
| 2 |
-
license: apache-2.0
|
| 3 |
-
language:
|
| 4 |
-
- en
|
| 5 |
base_model:
|
| 6 |
- PixArt-alpha/PixArt-XL-2-1024-MS
|
|
|
|
|
|
|
|
|
|
| 7 |
pipeline_tag: image-to-image
|
|
|
|
| 8 |
---
|
|
|
|
| 9 |
# 🎨 Cobra
|
| 10 |
|
| 11 |
**Efficient Line Art COlorization with BRoAder References**
|
|
|
|
| 1 |
---
|
|
|
|
|
|
|
|
|
|
| 2 |
base_model:
|
| 3 |
- PixArt-alpha/PixArt-XL-2-1024-MS
|
| 4 |
+
language:
|
| 5 |
+
- en
|
| 6 |
+
license: apache-2.0
|
| 7 |
pipeline_tag: image-to-image
|
| 8 |
+
library_name: diffusers
|
| 9 |
---
|
| 10 |
+
|
| 11 |
# 🎨 Cobra
|
| 12 |
|
| 13 |
**Efficient Line Art COlorization with BRoAder References**
|