Text-to-Image
Diffusers
flux
flux-diffusers
image-to-image
simpletuner
safe-for-work
lora
template:sd-lora
lycoris
Instructions to use quzo/iwatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quzo/iwatch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("quzo/iwatch") prompt = "unconditional (blank prompt)" image = pipe(prompt).images[0] - Inference
- 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: 0
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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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### emi-256
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- Repeats: 10
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- Total number of images: 22
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- Total number of aspect buckets:
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- Resolution: 0.065536 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: 0
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- Training steps: 2000
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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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### emi-256
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- Repeats: 10
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- Total number of images: 22
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- Total number of aspect buckets: 3
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- Resolution: 0.065536 megapixels
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- Cropped: False
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- Crop style: None
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