Image-to-Image
Diffusers
Safetensors
English
Image-to-Image
ControlNet
Diffusers
QwenImageControlNetPipeline
Qwen-Image
Instructions to use InstantX/Qwen-Image-ControlNet-Union with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/Qwen-Image-ControlNet-Union 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("InstantX/Qwen-Image-ControlNet-Union", 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
Update README.md
#4
by Frank1223 - opened
README.md
CHANGED
|
@@ -3,7 +3,7 @@ license: apache-2.0
|
|
| 3 |
language:
|
| 4 |
- en
|
| 5 |
library_name: diffusers
|
| 6 |
-
pipeline_tag:
|
| 7 |
tags:
|
| 8 |
- Image-to-Image
|
| 9 |
- ControlNet
|
|
@@ -118,4 +118,4 @@ For multiple conditions inference, please refer to [PR](https://github.com/huggi
|
|
| 118 |
We find that the model was unable to preserve some details without explicit 'TEXT' in prompt, such as small font text.
|
| 119 |
|
| 120 |
# Acknowledgements
|
| 121 |
-
This model is developed by InstantX Team. All copyright reserved.
|
|
|
|
| 3 |
language:
|
| 4 |
- en
|
| 5 |
library_name: diffusers
|
| 6 |
+
pipeline_tag: any-to-any
|
| 7 |
tags:
|
| 8 |
- Image-to-Image
|
| 9 |
- ControlNet
|
|
|
|
| 118 |
We find that the model was unable to preserve some details without explicit 'TEXT' in prompt, such as small font text.
|
| 119 |
|
| 120 |
# Acknowledgements
|
| 121 |
+
This model is developed by InstantX Team. All copyright reserved.
|