metadata
license: other
base_model: terminusresearch/FluxBooru-v0.3
tags:
- flux
- flux-diffusers
- text-to-image
- diffusers
- simpletuner
- not-for-all-audiences
- 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 photo of a q1s woman in a suit standing on the streets of Tokyo
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_1_0.png
- text: a anime of a q1s woman in school uniform standing on a bridge
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_2_0.png
- text: a photo of a q1s woman in leather jacket on the beach
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_3_0.png
- text: >-
A stunning portrait of a q1s woman adorned with a luxurious wide-brimmed
red hat that elegantly covers part of her face, illustration, vibrant,
sophisticated, portrait photography
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_4_0.png
- text: >-
A grainy, sepia-toned photograph taken with a Kodak Portra 400 film camera
in the late 1990s of a q1s woman with captivating gaze poses confidently.
She wears a vintage, black MinMin T-shirt, slightly oversized and slightly
worn, with the band's iconic logo prominently displayed. The background is
blurred, suggesting a dimly lit, underground music venue or a friend's
basement.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_5_0.png
- text: >-
A captivating minimalist masterpiece illustration of a q1s woman exuding
elegance and tranquility. The beautiful subject is dressed in a linen
dress, featuring pastel beige and light grey hues. The background consists
of a harmonious composition of rectangles and squares, subtly outlined in
black pencil. This vibrant and conceptual artwork elicits a cinematic and
fashionable illustration.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_6_0.png
- text: >-
a digital painting of a q1s woman in a green hoodie and purple skirt
standing in front of an office building
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_7_0.png
- text: >-
A whimsical miniature 3D alcohol ink portrait of a q1s woman mermaid
nestled in a giant seashell. She has a shimmering fish tail adorned with
intricate scales in various shades of blue and turquoise. She wears a top
made of tiny seashells and pearls. Surrounding her are small,
bioluminescent jellyfish, adding a magical glow to the scene. The lighting
creates a dreamy, underwater atmosphere that captures the essence of
oceanic wonder and enchantment.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_8_0.png
- text: a photo of a q1s woman as a historical marble statue in a grand bathroom
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_9_0.png
- text: >-
A captivating watercolor portrayal of a q1s woman. Her eyes are the focal
point. The vibrant color palette features bright red, deep green, and
pastel beige and white, creating a striking contrast. The fluid,
free-flowing brushstrokes imbue the artwork with movement and emotion. The
background is an abstract tapestry of color, with splashes of the same
hues, adding depth and dimension to the portrait. Painting, illustration.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_10_0.png
- text: an oil painting of q1s in a hoordie and skirt walking on the beach
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/image_11_0.png
flux-test-q1sV22
This is a LyCORIS adapter derived from terminusresearch/FluxBooru-v0.3.
The main validation prompt used during training was:
an oil painting of q1s in a hoordie and skirt walking on the beach
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: 6
- Training steps: 3400
- Learning rate: 0.001
- Max grad norm: 1.0
- Effective batch size: 3
- Micro-batch size: 1
- Gradient accumulation steps: 3
- Number of GPUs: 1
- Prediction type: flow-matching (extra parameters=['shift=1.0', 'flux_guidance_value=3.5', 'flux_attention_masked_training'])
- Optimizer: adamw_bf16weight_decay=1e-3
- Trainable parameter precision: Pure BF16
- Quantised base model: 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
q1sV22-1024-crop
- Repeats: 30
- Total number of images: 15
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
- Used for regularisation data: No
q1sV22-512-crop
- Repeats: 30
- Total number of images: 19
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
- Used for regularisation data: No
gen-and-inpaint-q1s-1024-reg
- Repeats: 0
- Total number of images: 530
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: center
- Crop aspect: square
- Used for regularisation data: Yes
Inference
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
def download_adapter(repo_id: str):
import os
from huggingface_hub import hf_hub_download
adapter_filename = "pytorch_lora_weights.safetensors"
cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
os.makedirs(path_to_adapter, exist_ok=True)
hf_hub_download(
repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
)
return path_to_adapter_file
model_id = 'terminusresearch/FluxBooru-v0.3'
adapter_repo_id = 'DragonQuix/flux-test-q1sV22'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()
prompt = "an oil painting of q1s in a hoordie and skirt walking on the beach"
## 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(1641421826),
width=1024,
height=1024,
guidance_scale=3.5,
).images[0]
image.save("output.png", format="PNG")