Model card auto-generated by SimpleTuner

README.md

@@ -0,0 +1,199 @@
+---
+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: 'jss_style, A woman sits slouched on a sofa beneath a mantelpiece, wrapped in blankets. Her eyes are closed, and her head rests on the back.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_1_0.png
+- text: 'jss_style, A man wearing a lavish robe holds a large, decorated sword. A young boy stands behind him, holding a cushion with a crown. They are in an ornate hall.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_2_0.png
+- text: 'jss_style, Three young girls in white aprons. One stands alone, two stand together by a large vase. A girl sits on the floor holding a doll. Large vases flank the scene.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_3_0.png
+- text: 'jss_style, hamster'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_4_0.png
+- text: 'jss_style, hipster making a chair'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_5_0.png
+- text: 'jss_style, A elegant woman in a long, black evening gown stands in a grand, dimly lit room. She has a confident pose, with one hand on her hip. A ornate gold frame mirror is visible in the background.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_6_0.png
+- text: 'jss_style, An opulent interior with a grand piano in the foreground. A woman in a white dress sits at the piano, her back to the viewer. Sunlight streams through tall windows.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_7_0.png
+- text: 'jss_style, A portrait of a modern tech CEO in a casual outfit, standing in front of a wall of computer screens'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_8_0.png
+- text: 'jss_style, A group portrait of a modern diverse family in a living room. Capture individual personalities while maintaining group cohesion.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_9_0.png
+- text: 'jss_style, A lively scene in a 1920s dance hall. Couples dancing, musicians playing, ambient lighting. Capture the movement and atmosphere in Sargent''s distinctive style.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_10_0.png
+- text: 'jss_style, People dining at tables outside a Parisian café.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_11_0.png
+- text: 'jss_style, A young boy holds a small black dog in his arms. He wears a red bow tie and stands in front of a textured backdrop. His red socks and shoes are notable.'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_12_0.png
+---
+
+# john-singer-sargent-sdxl-lora-03
+
+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:
+
+
+
+```
+jss_style, A young boy holds a small black dog in his arms. He wears a red bow tie and stands in front of a textured backdrop. His red socks and shoes are notable.
+```
+
+## Validation settings
+- CFG: `4.2`
+- CFG Rescale: `0.0`
+- Steps: `30`
+- 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:
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 0
+- Training steps: 250
+- 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
+
+### jss-sdxl-512
+- Repeats: 10
+- Total number of images: 84
+- Total number of aspect buckets: 7
+- Resolution: 0.262144 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### jss-sdxl-1024
+- Repeats: 10
+- Total number of images: 84
+- Total number of aspect buckets: 14
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### jss-sdxl-512-crop
+- Repeats: 10
+- Total number of images: 84
+- Total number of aspect buckets: 1
+- Resolution: 0.262144 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: square
+### jss-sdxl-1024-crop
+- Repeats: 10
+- Total number of images: 84
+- 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/john-singer-sargent-sdxl-lora-03'
+pipeline = DiffusionPipeline.from_pretrained(model_id)
+pipeline.load_lora_weights(adapter_id)
+
+prompt = "jss_style, A young boy holds a small black dog in his arms. He wears a red bow tie and stands in front of a textured backdrop. His red socks and shoes are notable."
+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=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=4.2,
+    guidance_rescale=0.0,
+).images[0]
+image.save("output.png", format="PNG")
+```
+