Instructions to use ddcu3eij/zxcv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ddcu3eij/zxcv with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("natsusakiyomi/SakuraMix", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ddcu3eij/zxcv") prompt = "zxcvv" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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## Model description
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zxcvb - pixiv rkgk style, trained on 6000 images, 1 epoch
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zxcvv - smug face style, trained on 230 images, 5 epoch
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use weight 0.5 - 0.6
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## Trigger words
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## Model description
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zxcvb - pixiv rkgk style, trained on 6000 images, 1 epoch
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zxcvv - smug face style, trained on 230 images, 5 epoch
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use weight 0.5 - 0.6
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## Trigger words
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