Instructions to use NO8D/ImagingControl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/ImagingControl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("NO8D/ImagingControl", dtype=torch.bfloat16, device_map="cuda") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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instance_prompt: null
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license:
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---
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# Slider-toolkit-Klein9B
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base_model:
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: https://bfl.ai/legal/non-commercial-license-terms
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# Slider-toolkit-Klein9B
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