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 Settings
- Draw Things
- DiffusionBee
Upload Qwen-Image-Edit-2509/config.json with huggingface_hub
Browse files
Qwen-Image-Edit-2509/config.json
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{
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"_class_name": "QwenImageTransformer2DModel",
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"_diffusers_version": "0.36.0.dev0",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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],
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"guidance_embeds": false,
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"in_channels": 64,
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"joint_attention_dim": 3584,
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"num_attention_heads": 24,
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"num_layers": 60,
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"out_channels": 16,
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"patch_size": 2
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}
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