markury's picture
Model card auto-generated by SimpleTuner
799138b verified
---
license: creativeml-openrail-m
base_model: "black-forest-labs/FLUX.1-dev"
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- simpletuner
- lora
- template:sd-lora
inference: true
widget:
- text: 'unconditional (blank prompt)'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_0_0.png
- text: 'unconditional (blank prompt)'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_1_1.png
- text: 'a photo of Brandon Rowland'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_2_0.png
- text: 'a photo of Brandon Rowland'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_3_1.png
- text: 'a photo of Brandon Rowland leaning against a brick wall, arms crossed, wearing a white tank top and ripped jeans. His gaze is intense, directed at the camera. The background includes a graffiti-covered wall and an urban street scene'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_4_0.png
- text: 'a photo of Brandon Rowland leaning against a brick wall, arms crossed, wearing a white tank top and ripped jeans. His gaze is intense, directed at the camera. The background includes a graffiti-covered wall and an urban street scene'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_5_1.png
- text: 'A photo of Brandon Rowland. Shirtless, lying on a dark blue sofa, one hand resting behind his head, the other on his chest. The background shows a bookshelf filled with books and plants. The lighting is dim, creating a cozy evening ambiance'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_6_0.png
- text: 'A photo of Brandon Rowland. Shirtless, lying on a dark blue sofa, one hand resting behind his head, the other on his chest. The background shows a bookshelf filled with books and plants. The lighting is dim, creating a cozy evening ambiance'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_7_1.png
- text: 'a photograph of Brandon Rowland'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_8_0.png
- text: 'a photograph of Brandon Rowland'
parameters:
negative_prompt: ''''
output:
url: ./assets/image_9_1.png
---
# brandon-rowland-flux
This is a 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 photograph of Brandon Rowland
```
## Validation settings
- CFG: `3.5`
- CFG Rescale: `0.0`
- Steps: `28`
- Sampler: `None`
- Seed: `420`
- Resolutions: `1024x1024,832x1216`
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: 200
- Training steps: 3000
- Learning rate: 0.0001
- Effective batch size: 2
- Micro-batch size: 1
- Gradient accumulation steps: 2
- Number of GPUs: 1
- Prediction type: flow-matching
- Rescaled betas zero SNR: False
- Optimizer: AdamW, stochastic bf16
- Precision: Pure BF16
- Xformers: Not used
- LoRA Rank: 16
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
## Datasets
### Brandon
- Repeats: 0
- Total number of images: 30
- Total number of aspect buckets: 7
- Resolution: 512 px
- Cropped: False
- Crop style: None
- Crop aspect: None
## Inference
```python
import torch
from diffusers import DiffusionPipeline
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'markury/brandon-rowland-flux'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "a photograph of Brandon Rowland"
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=28,
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=3.5,
).images[0]
image.save("output.png", format="PNG")
```