diffusers flux flux-diffusers text-to-image simpletuner safe-for-work lora template:sd-lora standard base_model:black-forest-labs/FLUX.1-dev base_model:adapter:black-forest-labs/FLUX.1-dev license:other region:us
---
base_model: black-forest-labs/FLUX.1-dev
license: other
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: A scene from My Hero Academia. Katsuki Bakugo holding a sign that says 'I
    LOVE PROMPTS!', he is standing full body on a beach at sunset. He is wearing his
    black and orange hero costume with grenade-like gauntlets on his arms. The setting
    sun casts a dynamic shadow on his determined expression.
  parameters:
    negative_prompt: blurry, cropped, ugly
  output:
    url: ./assets/image_1_0.png
- text: A scene from My Hero Academia. Katsuki Bakugo jumping out of a propeller airplane,
    sky diving. He looks intense and exhilarated, his spiky blonde hair blowing in
    the wind. The sky is clear and blue, with birds flying in the distance.
  parameters:
    negative_prompt: blurry, cropped, ugly
  output:
    url: ./assets/image_2_0.png
- text: 'A scene from My Hero Academia. Katsuki Bakugo spinning a basketball on his
    finger on a basketball court. He is wearing a Lakers jersey with the #12 on it.
    The basketball hoop and crowd are in the background cheering him. He is smirking
    confidently.'
  parameters:
    negative_prompt: blurry, cropped, ugly
  output:
    url: ./assets/image_3_0.png
- text: A scene from My Hero Academia. Katsuki Bakugo is wearing a suit in an office
    shaking the hand of a businesswoman. The woman has purple hair and is wearing
    professional attire. There is a Google logo in the background. It is during daytime,
    and the overall sentiment is one of fiery determination and success.
  parameters:
    negative_prompt: blurry, cropped, ugly
  output:
    url: ./assets/image_4_0.png
- text: A scene from My Hero Academia. Katsuki Bakugo is fighting a large brown grizzly
    bear, deep in a forest. The bear is tall and standing on two legs, roaring. The
    bear is also wearing a crown because it is the king of all bears. Around them
    are tall trees and other animals watching as Bakugo prepares to unleash an explosion.
  parameters:
    negative_prompt: blurry, cropped, ugly
  output:
    url: ./assets/image_5_0.png
---

# bakugo-standard-lora-1

This is a standard PEFT LoRA derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev).


No validation prompt was used during training.

None



## Validation settings
- CFG: `3.5`
- 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: 166
- Training steps: 3000
- Learning rate: 0.0001
  - Learning rate schedule: constant
  - Warmup steps: 100
- Max grad norm: 2.0
- Effective batch size: 48
  - Micro-batch size: 48
  - 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', 'flow_matching_loss=compatible', 'flux_lora_target=all'])
- Optimizer: adamw_bf16
- Trainable parameter precision: Pure BF16
- Caption dropout probability: 0.0%


- LoRA Rank: 128
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
    

## Datasets

### bakugo-512
- Repeats: 2
- Total number of images: 279
- Total number of aspect buckets: 1
- Resolution: 0.262144 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 = 'adipanda/bakugo-standard-lora-1'
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
pipeline.load_lora_weights(adapter_id)

prompt = "An astronaut is riding a horse through the jungles of Thailand."


## 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
image = 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=3.5,
).images[0]
image.save("output.png", format="PNG")
```



