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README.md

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+---
+license: other
+base_model: "black-forest-labs/FLUX.1-dev"
+tags:
+  - flux
+  - flux-diffusers
+  - text-to-image
+  - image-to-image
+  - diffusers
+  - simpletuner
+  - not-for-all-audiences
+  - lora
+
+  - template:sd-lora
+  - standard
+pipeline_tag: text-to-image
+inference: true
+widget:
+- text: 'unconditional (blank prompt)'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_0_0.png
+- text: 'a breathtaking anime-style portrait of nikolai, capturing his essence with vibrant colors and expressive features'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_1_0.png
+- text: 'a high-quality, detailed photograph of nikolai as a sous-chef, immersed in the art of culinary creation'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_2_0.png
+- text: 'a lifelike and intimate portrait of nikolai, showcasing his unique personality and charm'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_3_0.png
+- text: 'a cinematic, visually stunning photo of nikolai, emphasizing his dramatic and captivating presence'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_4_0.png
+- text: 'an elegant and timeless portrait of nikolai, exuding grace and sophistication'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_5_0.png
+- text: 'a dynamic and adventurous photo of nikolai, captured in an exciting, action-filled moment'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_6_0.png
+- text: 'a mysterious and enigmatic portrait of nikolai, shrouded in shadows and intrigue'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_7_0.png
+- text: 'a vintage-style portrait of nikolai, evoking the charm and nostalgia of a bygone era'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_8_0.png
+- text: 'an artistic and abstract representation of nikolai, blending creativity with visual storytelling'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_9_0.png
+- text: 'a futuristic and cutting-edge portrayal of nikolai, set against a backdrop of advanced technology'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_10_0.png
+- text: 'A picture of nikolai'
+  parameters:
+    negative_prompt: 'blurry, cropped, ugly'
+  output:
+    url: ./assets/image_11_0.png
+---
+
+# simpletuner-lora
+
+This is a 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:
+```
+A picture of nikolai
+```
+
+
+## Validation settings
+- CFG: `3.0`
+- CFG Rescale: `0.0`
+- Steps: `20`
+- Sampler: `FlowMatchEulerDiscreteScheduler`
+- Seed: `42`
+- Resolution: `1024x1024`
+- Skip-layer guidance: 
+
+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: 29
+- Training steps: 500
+- Learning rate: 0.0001
+  - Learning rate schedule: polynomial
+  - Warmup steps: 100
+- Max grad value: 1.0
+- Effective batch size: 1
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 1
+- Gradient checkpointing: True
+- Prediction type: flow_matching (extra parameters=['shift=3', 'flux_guidance_mode=constant', 'flux_guidance_value=1.0', 'flux_lora_target=mmdit'])
+- Optimizer: adamw_bf16
+- Trainable parameter precision: Pure BF16
+- Base model precision: `fp8-torchao`
+- Caption dropout probability: 0.1%
+
+
+- LoRA Rank: 16
+- LoRA Alpha: None
+- LoRA Dropout: 0.1
+- LoRA initialisation style: default
+- LoRA mode: Standard
+    
+
+## Datasets
+
+### dreambooth-subject
+- Repeats: 0
+- Total number of images: 17
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+
+model_id = 'black-forest-labs/FLUX.1-dev'
+adapter_id = 'codingrobot/simpletuner-lora'
+pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
+pipeline.load_lora_weights(adapter_id)
+
+prompt = "A picture of nikolai"
+
+
+## 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
+model_output = pipeline(
+    prompt=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(42),
+    width=1024,
+    height=1024,
+    guidance_scale=3.0,
+).images[0]
+
+model_output.save("output.png", format="PNG")
+
+```
+
+
+