flux-training-losercity-next-lycoris12
This is a LyCORIS adapter derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
loona from helluva boss is eating a donut
Validation settings
- CFG:
3.5
- CFG Rescale:
0.0
- Steps:
15
- Sampler:
None
- Seed:
42
- Resolution:
1024
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: 0
- Training steps: 2200
- Learning rate: 4e-05
- Effective batch size: 16
- Micro-batch size: 1
- Gradient accumulation steps: 16
- Number of GPUs: 1
- Prediction type: flow-matching
- Rescaled betas zero SNR: False
- Optimizer: adamw_bf16
- Precision: Pure BF16
- Quantised: Yes: fp8-quanto
- Xformers: Not used
- LyCORIS Config:
{
"algo": "lokr",
"multiplier": 1.0,
"linear_dim": 1000000,
"linear_alpha": 1,
"factor": 10,
"full_matrix": true,
"apply_preset": {
"target_module": [
"FluxTransformerBlock",
"FluxSingleTransformerBlock"
],
"name_algo_map": {
"transformer_blocks.[0-7]*": {
"algo": "lokr",
"factor": 4,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
},
"transformer_blocks.[8-15]*": {
"algo": "lokr",
"factor": 6,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
},
"transformer_blocks.[16-18]*": {
"algo": "lokr",
"factor": 12,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
},
"single_transformer_blocks.[0-15]*": {
"algo": "lokr",
"factor": 8,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
},
"single_transformer_blocks.[16-23]*": {
"algo": "lokr",
"factor": 6,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
},
"single_transformer_blocks.[24-37]*": {
"algo": "lokr",
"factor": 4,
"linear_dim": 1000000,
"linear_alpha": 1,
"full_matrix": true
}
},
"use_fnmatch": true
}
}
Datasets
default_dataset_arb
- Repeats: 9999
- Total number of images: 41
- Total number of aspect buckets: 1
- Resolution: 1.33 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
default_dataset_arb2
- Repeats: 9999
- Total number of images: 2565
- Total number of aspect buckets: 1
- Resolution: 1.33 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
default_dataset_arb3
- Repeats: 9999
- Total number of images: 3220
- Total number of aspect buckets: 1
- Resolution: 1.33 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
default_dataset
- Repeats: 9999
- Total number of images: 42
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_512
- Repeats: 9999
- Total number of images: 42
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_640
- Repeats: 9999
- Total number of images: 42
- Total number of aspect buckets: 1
- Resolution: 0.4096 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_768
- Repeats: 9999
- Total number of images: 42
- Total number of aspect buckets: 1
- Resolution: 0.589824 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_896
- Repeats: 9999
- Total number of images: 42
- Total number of aspect buckets: 1
- Resolution: 0.802816 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_uncaptioned
- Repeats: 9999
- Total number of images: 2565
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_uncaptioned_512
- Repeats: 9999
- Total number of images: 2565
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_art
- Repeats: 9999
- Total number of images: 2482
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_art_512
- Repeats: 9999
- Total number of images: 3193
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
default_dataset_art_640
- Repeats: 9999
- Total number of images: 3115
- Total number of aspect buckets: 1
- Resolution: 0.4096 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
default_dataset_art_768
- Repeats: 9999
- Total number of images: 2989
- Total number of aspect buckets: 1
- Resolution: 0.589824 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
default_dataset_art_896
- Repeats: 9999
- Total number of images: 2787
- Total number of aspect buckets: 1
- Resolution: 0.802816 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
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 = "loona from helluva boss is eating a donut"
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=15,
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")
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Model tree for jimmycarter/flux-training-losercity-next-lycoris12
Base model
black-forest-labs/FLUX.1-dev