--- license: creativeml-openrail-m base_model: stabilityai/stable-diffusion-3-medium-diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - simpletuner - lora - template:sd-lora - not-for-all-audiences inference: true widget: - text: unconditional (blank prompt) parameters: negative_prompt: blurry, cropped, ugly output: url: ./assets/image_0_0.png - text: a photo of a naked woman with large breasts parameters: negative_prompt: blurry, cropped, ugly output: url: ./assets/image_1_0.png --- # sdxl-training This is a LoRA derived from [stabilityai/stable-diffusion-3-medium-diffusers](https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers). The main validation prompt used during training was: ``` a naked woman, front view, standing in a room. large breasts, pretty face, pussy. photo, RAW candid cinema, 16mm, color graded portra 400 film, remarkable color, ultra realistic, dry skin, shot with cinematic camera ``` Negative prompt: ``` ugly 3d render, deformed corpse, brushstrokes, painting ``` ## Validation settings - CFG: `4.0` - CFG Rescale: `0.0` - Steps: `40` - Sampler: `euler` - Seed: `6` - Resolution: `816x1280` Note: The validation settings are not necessarily the same as the [training settings](#training-settings). You can find some example images in the following gallery: The text encoder **was not** trained. You may reuse the base model text encoder for inference. ## Training settings - Training epochs: 1072 - Training steps: 21450 - Learning rate: 0.0002 - Effective batch size: 20 - Micro-batch size: 5 - Gradient accumulation steps: 4 - Number of GPUs: 1 - Prediction type: epsilon - Rescaled betas zero SNR: False - Optimizer: AdamW, stochastic bf16 - Precision: Pure BF16 - Xformers: Enabled - LoRA Rank: 64 - LoRA Alpha: 64.0 - LoRA Dropout: 0.1 - LoRA initialisation style: default ## Datasets ### curated3 - Repeats: 0 - Total number of images: 400 - Total number of aspect buckets: 1 - Resolution: 0.5 megapixels - Cropped: False - Crop style: None - Crop aspect: None