--- license: creativeml-openrail-m base_model: "stabilityai/stable-diffusion-xl-base-1.0" tags: - sdxl - sdxl-diffusers - text-to-image - diffusers - simpletuner - safe-for-work - lora - template:sd-lora - standard inference: true widget: - text: 'unconditional (blank prompt)' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_0_0.png - text: 'hshge, Mount Fuji viewed from a distance, with cherry blossoms in the foreground. A small village nestles at the base of the mountain.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_1_0.png - text: 'hshge, Hamster' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_2_0.png - text: 'hshge, A scene from the Tokaido road, with travelers crossing a wooden bridge. A misty mountain landscape in the background.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_3_0.png - text: 'hshge, A busy fish market in Edo. Vendors display their catch while customers browse. Boats visible in the nearby harbor.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_4_0.png - text: 'hshge, People caught in a sudden rainstorm on a city street, rushing for cover with umbrellas. A large bridge spans the background.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_5_0.png - text: 'hshge, A serene temple complex under a full moon. Lanterns illuminate the path, with silhouettes of pine trees against the night sky.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_6_0.png - text: 'hshge, A traditional Japanese garden in winter. Snow-covered trees and a small bridge over a frozen pond. A figure in a kimono walks along a path.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_7_0.png - text: 'hshge, The modern Tokyo Skytree towering over traditional low-rise buildings. Cherry blossoms frame the view.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_8_0.png - text: 'hshge, A sleek bullet train speeding past Mount Fuji. Rice fields and a small town visible in the middle ground.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_9_0.png - text: 'hshge, The bustling Times Square in New York, with bright billboards and crowds of people. A view reminiscent of Hiroshige''s busy street scenes.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_10_0.png - text: 'hshge, A futuristic Mars colony with dome habitats and space vehicles. The red Martian landscape stretches to the horizon.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_11_0.png - text: 'hshge, An imaginary underwater city with Japanese-style architecture. Fish and sea creatures swim among the buildings.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_12_0.png - text: 'hshge, People wearing VR headsets in a modern cafe. Traditional Japanese elements mix with futuristic technology in the decor.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_13_0.png - text: 'hshge, hamster' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_14_0.png --- # Hiroshige-SDXL-LoRA This is a standard PEFT LoRA derived from [stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0). The main validation prompt used during training was: ``` hshge, hamster ``` ## Validation settings - CFG: `4.2` - CFG Rescale: `0.0` - Steps: `20` - Sampler: `None` - Seed: `42` - Resolution: `1024x1024` 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: 7 - Training steps: 10000 - Learning rate: 8e-05 - Effective batch size: 8 - Micro-batch size: 8 - Gradient accumulation steps: 1 - Number of GPUs: 1 - Prediction type: epsilon - Rescaled betas zero SNR: False - Optimizer: adamw_bf16 - Precision: Pure BF16 - Quantised: Yes: int8-quanto - Xformers: Not used - LoRA Rank: 64 - LoRA Alpha: None - LoRA Dropout: 0.1 - LoRA initialisation style: default ## Datasets ### hiroshige-sdxl-512 - Repeats: 10 - Total number of images: 219 - Total number of aspect buckets: 10 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None ### hiroshige-sdxl-1024 - Repeats: 10 - Total number of images: 219 - Total number of aspect buckets: 16 - Resolution: 1.048576 megapixels - Cropped: False - Crop style: None - Crop aspect: None ### hiroshige-sdxl-512-crop - Repeats: 10 - Total number of images: 219 - Total number of aspect buckets: 1 - Resolution: 0.262144 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### hiroshige-sdxl-1024-crop - Repeats: 10 - Total number of images: 219 - Total number of aspect buckets: 1 - Resolution: 1.048576 megapixels - Cropped: True - Crop style: random - Crop aspect: square ## Inference ```python import torch from diffusers import DiffusionPipeline model_id = 'stabilityai/stable-diffusion-xl-base-1.0' adapter_id = 'davidrd123/Hiroshige-SDXL-LoRA' pipeline = DiffusionPipeline.from_pretrained(model_id) pipeline.load_lora_weights(adapter_id) prompt = "hshge, hamster" negative_prompt = 'blurry, cropped, ugly' pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') image = pipeline( prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=20, 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=4.2, guidance_rescale=0.0, ).images[0] image.save("output.png", format="PNG") ```