Instructions to use diffusers/Qwen-Image-Layered-modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/Qwen-Image-Layered-modular with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/Qwen-Image-Layered-modular", 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
- Draw Things
- DiffusionBee
Update modular_model_index.json
Browse files- modular_model_index.json +4 -4
modular_model_index.json
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{
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"pretrained_model_name_or_path": "
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"revision": null,
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"subfolder": "
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"type_hint": [
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"transformers",
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"Qwen2_5_VLForConditionalGeneration"
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"pretrained_model_name_or_path": "
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"revision": null,
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"subfolder": "
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"type_hint": [
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"diffusers",
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"QwenImageTransformer2DModel"
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{
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"pretrained_model_name_or_path": "OzzyGT/qwen-image-layered-bnb-4bit-text-encoder",
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"revision": null,
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"subfolder": "",
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"type_hint": [
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"transformers",
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"Qwen2_5_VLForConditionalGeneration"
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{
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"pretrained_model_name_or_path": "OzzyGT/qwen-image-layered-bnb-4bit-transformer",
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"revision": null,
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"subfolder": "",
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"type_hint": [
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"diffusers",
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"QwenImageTransformer2DModel"
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