metadata
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
- lycoris
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_0_0.png
- text: >-
A scene from Chainsaw Man. Makima holding a sign that says 'I LOVE
PROMPTS!', she is standing full body on a beach at sunset. She is wearing
a a white shirt, black tie, and black coat. The setting sun casts a
dynamic shadow on her face.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
- text: >-
A scene from Chainsaw Man. Makima jumping out of a propeller airplane, sky
diving. She looks excited and her hair is blowing in the wind. The sky is
clear and blue, there are birds pictured in the distance.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_0.png
- text: >-
A scene from Chainsaw Man. Makima spinning a basketball on her finger on a
basketball court. She is wearing a lakers jersey with the #12 on it. The
basketball hoop and crowd are in the background cheering for her. She is
smiling.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
A scene from Chainsaw Man. Makima is wearing a suit in an office shaking
the hand of a business man. The man 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 accomplishment.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_0.png
- text: >-
A scene from Chainsaw Man. Makima 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.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_5_0.png
makima-simpletuner-lora-1
This is a LyCORIS adapter derived from 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:
None
- Seed:
42
- Resolution:
1024x1024
Note: The validation settings are not necessarily the same as the training settings.
You can find some example images in the following gallery:
The text encoder was not trained. You may reuse the base model text encoder for inference.
Training settings
- Training epochs: 306
- Training steps: 7000
- Learning rate: 0.0002
- Effective batch size: 32
- Micro-batch size: 32
- 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
- LyCORIS Config:
{
"algo": "lokr",
"multiplier": 1.0,
"linear_dim": 10000,
"linear_alpha": 1,
"factor": 12,
"apply_preset": {
"target_module": [
"Attention",
"FeedForward"
],
"module_algo_map": {
"Attention": {
"factor": 12
},
"FeedForward": {
"factor": 6
}
}
}
}
Datasets
makima-512
- Repeats: 2
- Total number of images: 164
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
Inference
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'pytorch_lora_weights.safetensors' # you will have to download this manually
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
wrapper.merge_to()
prompt = "An astronaut is riding a horse through the jungles of Thailand."
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=20,
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")