metadata

license: other
base_model: stabilityai/stable-diffusion-3.5-large
tags:
  - sd3
  - sd3-diffusers
  - text-to-image
  - diffusers
  - simpletuner
  - not-for-all-audiences
  - lora
  - template:sd-lora
  - lycoris
inference: true
widget:
  - text: unconditional (blank prompt)
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_0_0.png
  - text: >-
      emaSde3Ver1, a high-resolution photograph featuring a young caucasian
      woman with long, wavy, platinum blonde hair cascading over her shoulders,
      she has a slender yet curvaceous physique with prominent breasts and a
      small waist, her skin is fair and smooth, with a slight blush on her
      cheeks, giving her a sultry expression, she is wearing a sheer, black
      fishnet bodysuit that accentuates her curves, with her back to the viewer,
      revealing her lower back and buttocks, the bodice is made of a soft,
      textured fabric that clings to her body, emphasizing her curves and the
      texture of the fishnet fabric, she also wears a black choker around her
      neck, adding a touch of sensuality to her attire, the background features
      a blurred, out-of-focus view of a cityscape with distant mountains and a
      clear blue sky, suggesting an outdoor setting, the balcony she is standing
      on has wooden railings and a wooden railing, adding to the sense of a
      balcony or terrace, the overall mood of the photograph is sensual and
      intimate, emphasizing the subject's allure and beauty
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_1_0.png

sd35-training

This is a LyCORIS adapter derived from stabilityai/stable-diffusion-3.5-large.

The main validation prompt used during training was:

emaSde3Ver1, a high-resolution photograph featuring a young caucasian woman with long, wavy, platinum blonde hair cascading over her shoulders, she has a slender yet curvaceous physique with prominent breasts and a small waist, her skin is fair and smooth, with a slight blush on her cheeks, giving her a sultry expression, she is wearing a sheer, black fishnet bodysuit that accentuates her curves, with her back to the viewer, revealing her lower back and buttocks, the bodice is made of a soft, textured fabric that clings to her body, emphasizing her curves and the texture of the fishnet fabric, she also wears a black choker around her neck, adding a touch of sensuality to her attire, the background features a blurred, out-of-focus view of a cityscape with distant mountains and a clear blue sky, suggesting an outdoor setting, the balcony she is standing on has wooden railings and a wooden railing, adding to the sense of a balcony or terrace, the overall mood of the photograph is sensual and intimate, emphasizing the subject's allure and beauty

Validation settings

CFG: 5.0
CFG Rescale: 0.0
Steps: 30
Sampler: None
Seed: 42
Resolution: 1024

Note: The validation settings are not necessarily the same as the training settings.

You can find some example images in the following gallery:

Prompt
unconditional (blank prompt)

Negative Prompt
blurry, cropped, ugly

Prompt
emaSde3Ver1, a high-resolution photograph featuring a young caucasian woman with long, wavy, platinum blonde hair cascading over her shoulders, she has a slender yet curvaceous physique with prominent breasts and a small waist, her skin is fair and smooth, with a slight blush on her cheeks, giving her a sultry expression, she is wearing a sheer, black fishnet bodysuit that accentuates her curves, with her back to the viewer, revealing her lower back and buttocks, the bodice is made of a soft, textured fabric that clings to her body, emphasizing her curves and the texture of the fishnet fabric, she also wears a black choker around her neck, adding a touch of sensuality to her attire, the background features a blurred, out-of-focus view of a cityscape with distant mountains and a clear blue sky, suggesting an outdoor setting, the balcony she is standing on has wooden railings and a wooden railing, adding to the sense of a balcony or terrace, the overall mood of the photograph is sensual and intimate, emphasizing the subject's allure and beauty

Negative Prompt
blurry, cropped, ugly

The text encoder was not trained. You may reuse the base model text encoder for inference.

Training settings

Training epochs: 139
Training steps: 3500
Learning rate: 0.0001
Max grad norm: 0.01
Effective batch size: 2
- Micro-batch size: 2
- Gradient accumulation steps: 1
- Number of GPUs: 1
Prediction type: flow-matching (extra parameters=['shift=3'])
Rescaled betas zero SNR: False
Optimizer: adamw_bf16
Precision: Pure BF16
Quantised: Yes: int8-quanto
Xformers: Not used
LyCORIS Config:

{
    "bypass_mode": true,
    "algo": "lokr",
    "multiplier": 1.0,
    "full_matrix": true,
    "linear_dim": 10000,
    "linear_alpha": 1,
    "factor": 12,
    "apply_preset": {
        "target_module": [
            "Attention"
        ],
        "module_algo_map": {
            "Attention": {
                "factor": 6
            }
        }
    }
}

Datasets

emaSde3Ver1

Repeats: 0
Total number of images: 50
Total number of aspect buckets: 1
Resolution: 1.0 megapixels
Cropped: true
Crop style: center
Crop aspect: square
Used for regularisation data: No

Inference

import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights


def download_adapter(repo_id: str):
    import os
    from huggingface_hub import hf_hub_download
    adapter_filename = "pytorch_lora_weights.safetensors"
    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
    os.makedirs(path_to_adapter, exist_ok=True)
    hf_hub_download(
        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
    )

    return path_to_adapter_file
    
model_id = 'stabilityai/stable-diffusion-3.5-large'
adapter_repo_id = 'alexnvo/sd35-training'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()

prompt = "emaSde3Ver1, a high-resolution photograph featuring a young caucasian woman with long, wavy, platinum blonde hair cascading over her shoulders, she has a slender yet curvaceous physique with prominent breasts and a small waist, her skin is fair and smooth, with a slight blush on her cheeks, giving her a sultry expression, she is wearing a sheer, black fishnet bodysuit that accentuates her curves, with her back to the viewer, revealing her lower back and buttocks, the bodice is made of a soft, textured fabric that clings to her body, emphasizing her curves and the texture of the fishnet fabric, she also wears a black choker around her neck, adding a touch of sensuality to her attire, the background features a blurred, out-of-focus view of a cityscape with distant mountains and a clear blue sky, suggesting an outdoor setting, the balcony she is standing on has wooden railings and a wooden railing, adding to the sense of a balcony or terrace, the overall mood of the photograph is sensual and intimate, emphasizing the subject's allure and beauty"
negative_prompt = 'blurry, cropped, ugly'

## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
    
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
image = pipeline(
    prompt=prompt,
    negative_prompt=negative_prompt,
    num_inference_steps=30,
    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
    width=1024,
    height=1024,
    guidance_scale=5.0,
).images[0]
image.save("output.png", format="PNG")