Instructions to use jimchoi/simpletuner-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jimchoi/simpletuner-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jimchoi/simpletuner-lora") prompt = "A swift and agile elven archer perched in a tree, nocking an arrow." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Model card auto-generated by SimpleTuner
Browse files
README.md
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## Training settings
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- Training epochs: 6
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- Training steps:
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- Learning rate: 0.0001
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- Learning rate schedule: polynomial
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- Warmup steps: 100
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### wikiart_sargent
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- Repeats: 0
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- Total number of images: 920
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- Total number of aspect buckets:
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- Resolution: 1.048576 megapixels
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- Cropped: False
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- Crop style: None
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## Training settings
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- Training epochs: 6
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- Training steps: 6200
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- Learning rate: 0.0001
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- Learning rate schedule: polynomial
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- Warmup steps: 100
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### wikiart_sargent
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- Repeats: 0
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- Total number of images: 920
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- Total number of aspect buckets: 4
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- Resolution: 1.048576 megapixels
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- Cropped: False
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- Crop style: None
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