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--- |
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license: other |
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base_model: "stabilityai/stable-diffusion-3.5-large" |
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tags: |
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- sd3 |
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- sd3-diffusers |
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- text-to-image |
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- diffusers |
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- simpletuner |
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- not-for-all-audiences |
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- lora |
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- template:sd-lora |
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- standard |
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inference: true |
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widget: |
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- text: 'unconditional (blank prompt)' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_0_0.png |
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- text: 'your prompt to validate on' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_1_0.png |
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- text: 'another prompt to validate on' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_2_0.png |
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- text: 'your main test prompt here' |
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parameters: |
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negative_prompt: 'blurry, cropped, ugly' |
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output: |
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url: ./assets/image_3_0.png |
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--- |
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# simpletuner-lora |
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This is a standard PEFT LoRA derived from [stabilityai/stable-diffusion-3.5-large](https://huggingface.co/stabilityai/stable-diffusion-3.5-large). |
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The main validation prompt used during training was: |
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``` |
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your main test prompt here |
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``` |
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## Validation settings |
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- CFG: `3.0` |
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- CFG Rescale: `0.0` |
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- Steps: `20` |
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- Sampler: `None` |
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- Seed: `42` |
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- Resolution: `512x512` |
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Note: The validation settings are not necessarily the same as the [training settings](#training-settings). |
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You can find some example images in the following gallery: |
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<Gallery /> |
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The text encoder **was not** trained. |
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You may reuse the base model text encoder for inference. |
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## Training settings |
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- Training epochs: 2 |
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- Training steps: 10000 |
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- Learning rate: 0.0001 |
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- Max grad norm: 0.01 |
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- Effective batch size: 8 |
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- Micro-batch size: 1 |
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- Gradient accumulation steps: 1 |
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- Number of GPUs: 8 |
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- Prediction type: flow-matching |
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- Rescaled betas zero SNR: False |
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- Optimizer: adamw_bf16 |
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- Precision: Pure BF16 |
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- Quantised: No |
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- Xformers: Not used |
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- LoRA Rank: 16 |
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- LoRA Alpha: None |
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- LoRA Dropout: 0.1 |
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- LoRA initialisation style: default |
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## Datasets |
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### richhf_18k |
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- Repeats: 1 |
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- Total number of images: ~15816 |
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- Total number of aspect buckets: 1 |
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- Resolution: 512 px |
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- Cropped: False |
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- Crop style: None |
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- Crop aspect: None |
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- Used for regularisation data: No |
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## Inference |
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```python |
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import torch |
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from diffusers import DiffusionPipeline |
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model_id = 'stabilityai/stable-diffusion-3.5-large' |
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adapter_id = 'luoyan227/simpletuner-lora' |
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pipeline = DiffusionPipeline.from_pretrained(model_id) |
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pipeline.load_lora_weights(adapter_id) |
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prompt = "your main test prompt here" |
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negative_prompt = 'blurry, cropped, ugly' |
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pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') |
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image = pipeline( |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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num_inference_steps=20, |
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generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826), |
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width=512, |
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height=512, |
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guidance_scale=3.0, |
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).images[0] |
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image.save("output.png", format="PNG") |
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``` |
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