Model card auto-generated by SimpleTuner

README.md

@@ -0,0 +1,142 @@
+---
+license: other
+base_model: "black-forest-labs/FLUX.1-dev"
+tags:
+  - flux
+  - flux-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: 'photo of a modern architectural interior event space at dusk'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_1_0.png
+---
+
+# simpletuner-lora-spindrift
+
+This is a standard PEFT LoRA derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev).
+
+
+The main validation prompt used during training was:
+
+
+
+```
+photo of a modern architectural interior event space at dusk
+```
+
+## Validation settings
+- CFG: `3.0`
+- CFG Rescale: `0.0`
+- Steps: `25`
+- Sampler: `None`
+- Seed: `42`
+- Resolution: `1216x832`
+
+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: 1000
+- Learning rate: 1e-05
+- Effective batch size: 1
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 1
+- Prediction type: flow-matching
+- 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
+
+### spindrift-dataset-512
+- Repeats: 25
+- Total number of images: 29
+- Total number of aspect buckets: 6
+- Resolution: 0.262144 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### spindrift-dataset-1024
+- Repeats: 25
+- Total number of images: 32
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### spindrift-dataset-512-crop
+- Repeats: 25
+- Total number of images: 32
+- Total number of aspect buckets: 1
+- Resolution: 0.262144 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: square
+### spindrift-dataset-1024-crop
+- Repeats: 25
+- Total number of images: 32
+- 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 = 'black-forest-labs/FLUX.1-dev'
+adapter_id = 'spawn99/simpletuner-lora-spindrift'
+pipeline = DiffusionPipeline.from_pretrained(model_id)
+pipeline.load_lora_weights(adapter_id)
+
+prompt = "photo of a modern architectural interior event space at dusk"
+
+pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
+image = pipeline(
+    prompt=prompt,
+    num_inference_steps=25,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
+    width=1216,
+    height=832,
+    guidance_scale=3.0,
+).images[0]
+image.save("output.png", format="PNG")
+```
+