Datasets:
License:
Upload folder using huggingface_hub
Browse files- README.md +132 -0
- assets/image_0_0.png +3 -0
- assets/image_1_0.png +3 -0
- optimizer.bin +3 -0
- pytorch_lora_weights.safetensors +3 -0
- random_states_0.pkl +3 -0
- scheduler.bin +3 -0
- training_state-bucky-annotated-2.json +1 -0
- training_state.json +1 -0
README.md
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---
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license: other
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base_model: "stabilityai/stable-diffusion-3.5-medium"
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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: 'Baky tuxedo cat, resting on top of a table, looking to the camera, paws tucked'
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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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---
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# sd35-bucky_v7
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This is a standard PEFT LoRA derived from [stabilityai/stable-diffusion-3.5-medium](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium).
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The main validation prompt used during training was:
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```
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Baky tuxedo cat, resting on top of a table, looking to the camera, paws tucked
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```
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## Validation settings
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- CFG: `7.5`
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- CFG Rescale: `0.0`
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- Steps: `10`
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- Sampler: `FlowMatchEulerDiscreteScheduler`
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- Seed: `4201`
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- Resolution: `1024`
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- Skip-layer guidance:
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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: 5
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- Training steps: 640
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- Learning rate: 0.0002
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- Learning rate schedule: polynomial
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- Warmup steps: 64
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- Max grad norm: 2.0
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- Effective batch size: 2
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- Micro-batch size: 2
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- Gradient accumulation steps: 1
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- Number of GPUs: 1
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- Gradient checkpointing: True
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- Prediction type: flow-matching (extra parameters=['shift=3'])
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- Optimizer: adamw_bf16
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- Trainable parameter precision: Pure BF16
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- Caption dropout probability: 0.0%
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- LoRA Rank: 768
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- LoRA Alpha: 768.0
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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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### bucky-annotated-2
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- Repeats: 1
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- Total number of images: 120
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- Total number of aspect buckets: 2
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- Resolution: 1.0 megapixels
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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-medium'
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adapter_id = 'jwnt4/sd35-bucky_v7'
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pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
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pipeline.load_lora_weights(adapter_id)
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prompt = "Baky tuxedo cat, resting on top of a table, looking to the camera, paws tucked"
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negative_prompt = 'blurry, cropped, ugly'
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## Optional: quantise the model to save on vram.
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## Note: The model was not quantised during training, so it is not necessary to quantise it during inference time.
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#from optimum.quanto import quantize, freeze, qint8
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#quantize(pipeline.transformer, weights=qint8)
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#freeze(pipeline.transformer)
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pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
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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=10,
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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(4201),
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width=1024,
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height=1024,
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guidance_scale=7.5,
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).images[0]
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image.save("output.png", format="PNG")
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```
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assets/image_0_0.png
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Git LFS Details
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assets/image_1_0.png
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Git LFS Details
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optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e13a535d4942e56900c3794d7583cb6969d575622627b6477cf55201c34f281c
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size 2095322810
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1bdb6bfe05ac70d957ac6fba947ce46d1a411bc815fb5f8a297ba77647642bc8
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size 698391168
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random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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size 14344
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scheduler.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7cc91ab082e5b7dfbe28b4d0051da1b7c7f593c55c5e31b4949bfb72e3385595
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size 1000
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training_state-bucky-annotated-2.json
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{"aspect_ratio_bucket_indices": {"0.78": ["/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_05_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_75_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_61_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_70_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_09_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_05_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_59_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_70_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_50_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_50_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_59_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_76_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_24_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_62_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_59_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_24_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_61_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_38_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_28_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_59_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_47_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_50_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_76_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_09_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_24_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_76_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_44_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_75_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_28_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_47_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_69_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_52_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_70_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_47_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_38_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_05_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_62_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_62_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_38_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_24_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_72_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_38_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_72_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_69_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_09_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_52_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_75_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_72_1.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_62_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_50_3.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_70_4.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_28_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_61_2.jpg", "/home/cat-storybook-sd3.5/datasets/bucky-annotated-2-duplicate-shuffle/bucky_44_3.jpg", 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training_state.json
ADDED
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{"global_step": 640, "epoch_step": 645, "epoch": 6, "exhausted_backends": [], "repeats": {"bucky-annotated-2": 0}}
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