Text-to-Image
Diffusers
Safetensors
English
QuantFuncPipeline
custom_qwen_image
image-generation
diffusion
quantized
quantfunc
Instructions to use QuantFunc/Qwen-Image-Series with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QuantFunc/Qwen-Image-Series with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("QuantFunc/Qwen-Image-Series", 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
Upload README.md with huggingface_hub
Browse files
README.md
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library_name: diffusers
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frameworks:
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- pytorch
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language:
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- en
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license: other
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license_name: quantfunc-model-license
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tags:
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- image-generation
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- text-to-image
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- diffusion
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- quantized
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- quantfunc
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pipeline_tag: text-to-image
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language:
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- en
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license: other
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license_name: quantfunc-model-license
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tags:
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- image-generation
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- text-to-image
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- diffusion
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- quantized
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- quantfunc
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- qwen
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library_name: diffusers
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pipeline_tag: text-to-image
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