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--- |
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license: other |
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base_model: "black-forest-labs/FLUX.1-dev" |
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tags: |
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- flux |
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- flux-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: '''' |
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output: |
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url: ./assets/image_0_0.png |
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- text: 'A black tabby dog.' |
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parameters: |
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negative_prompt: '''' |
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output: |
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url: ./assets/image_1_0.png |
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--- |
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# clayygodd/flux-lora-training |
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This is a standard PEFT LoRA derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev). |
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The main validation prompt used during training was: |
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``` |
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A black tabby dog. |
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``` |
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## Validation settings |
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- CFG: `3.5` |
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- CFG Rescale: `0.0` |
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- Steps: `15` |
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- Sampler: `None` |
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- Seed: `42` |
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- Resolution: `1024x1024` |
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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: 33 |
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- Training steps: 200 |
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- Learning rate: 0.0001 |
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- Effective batch size: 4 |
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- Micro-batch size: 4 |
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- Gradient accumulation steps: 1 |
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- Number of GPUs: 1 |
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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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### default_dataset |
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- Repeats: 0 |
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- Total number of images: 24 |
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- Total number of aspect buckets: 1 |
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- Resolution: 1.048576 megapixels |
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- Cropped: True |
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- Crop style: center |
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- Crop aspect: square |
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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 = 'black-forest-labs/FLUX.1-dev' |
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adapter_id = 'clayygodd/clayygodd/flux-lora-training' |
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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 = "A black tabby dog." |
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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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num_inference_steps=15, |
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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=1024, |
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height=1024, |
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guidance_scale=3.5, |
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).images[0] |
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image.save("output.png", format="PNG") |
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``` |
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