Text-to-Image
Diffusers
TensorBoard
diffusers-training
dora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use J1k/train_return with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use J1k/train_return with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("J1k/train_return", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of pattern fabic" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
패턴 원단 train
Browse files
README.md
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- template:sd-lora
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a photo of pattern fabic
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widget: []
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- template:sd-lora
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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- text-to-image
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- text-to-image
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- diffusers-training
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- diffusers
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- dora
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- template:sd-lora
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a photo of pattern fabic
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widget: []
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