Instructions to use EnD-Diffusers/wave-concepts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/wave-concepts with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/wave-concepts", dtype=torch.bfloat16, device_map="cuda") prompt = "wvebg1" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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license: creativeml-openrail-m
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tags:
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- text-to-image
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widget:
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- text: wvebg1
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---
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### Wave Concepts Dreambooth model trained by Duskfallcrew with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model
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wvebg1 (use that on your prompt)
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license: creativeml-openrail-m
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tags:
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- text-to-image
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- vaporwave
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- backgrounds
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- synthwave
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widget:
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language:
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- en
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pipeline_tag: text-to-image
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---
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### Wave Concepts Dreambooth model trained by Duskfallcrew with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model
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wvebg1 (use that on your prompt)
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