Instructions to use OPPOer/Qwen-Image-13B-8steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OPPOer/Qwen-Image-13B-8steps with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OPPOer/Qwen-Image-13B-8steps", 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 Settings
- Draw Things
- DiffusionBee
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -31,11 +31,6 @@ This open-source project is based on Qwen-Image and has attempted model pruning,
|
|
| 31 |
|
| 32 |
## Quick Start
|
| 33 |
|
| 34 |
-
Download the file transformer_qwenimage_pruning.py from **https://github.com/OPPO-Mente-Lab/Qwen-Image-Pruning** to your local directory, and then you can directly load model with
|
| 35 |
-
```python
|
| 36 |
-
DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
|
| 37 |
-
```
|
| 38 |
-
|
| 39 |
Install the latest version of diffusers and pytorch
|
| 40 |
```
|
| 41 |
pip install torch
|
|
|
|
| 31 |
|
| 32 |
## Quick Start
|
| 33 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 34 |
Install the latest version of diffusers and pytorch
|
| 35 |
```
|
| 36 |
pip install torch
|