Instructions to use lightx2v/Qwen-Image-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Qwen-Image-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Qwen-Image-Lightning") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Fix tags (#30)
Browse files- Fix tags (f426926366e9131908e3c4685da1ead8d3b62f46)
Co-authored-by: 🎬cinema_anon <qpqpqpqpqpqp@users.noreply.huggingface.co>
README.md
CHANGED
|
@@ -7,8 +7,8 @@ base_model:
|
|
| 7 |
- Qwen/Qwen-Image
|
| 8 |
pipeline_tag: text-to-image
|
| 9 |
tags:
|
| 10 |
-
- Qwen-Image
|
| 11 |
-
- distillation
|
| 12 |
- LoRA
|
| 13 |
- lora
|
| 14 |
library_name: diffusers
|
|
|
|
| 7 |
- Qwen/Qwen-Image
|
| 8 |
pipeline_tag: text-to-image
|
| 9 |
tags:
|
| 10 |
+
- Qwen-Image
|
| 11 |
+
- distillation
|
| 12 |
- LoRA
|
| 13 |
- lora
|
| 14 |
library_name: diffusers
|