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---
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
- standard
inference: true
widget:
- text: 'unconditional (blank prompt)'
parameters:
negative_prompt: 'blurry, cropped, ugly'
output:
url: ./assets/image_0_0.png
- text: 'This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine''s steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine''s drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors.'
parameters:
negative_prompt: 'blurry, cropped, ugly'
output:
url: ./assets/image_1_0.png
---
# jazzy-st
This is a standard PEFT 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:
```
This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine's steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine's drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors.
```
## Validation settings
- CFG: `3.0`
- 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](#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: 4
- Training steps: 5000
- Learning rate: 0.0004
- Max grad norm: 2.0
- Effective batch size: 1
- Micro-batch size: 1
- Gradient accumulation steps: 1
- Number of GPUs: 1
- Prediction type: flow-matching (extra parameters=['shift=3', 'flux_guidance_value=1.0', 'flux_lora_target=all'])
- Rescaled betas zero SNR: False
- Optimizer: adamw_bf16
- Precision: Pure BF16
- Quantised: No
- Xformers: Not used
- LoRA Rank: 64
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
## Datasets
### jazzy-512
- Repeats: 10
- Total number of images: 28
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### jazzy-1024
- Repeats: 10
- Total number of images: 28
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### jazzy-512-crop
- Repeats: 10
- Total number of images: 28
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
- Used for regularisation data: No
### jazzy-1024-crop
- Repeats: 10
- Total number of images: 28
- Total number of aspect buckets: 1
- Resolution: 1.048576 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
- Used for regularisation data: No
## Inference
```python
import torch
from diffusers import DiffusionPipeline
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'linhqyy/jazzy-st'
pipeline = DiffusionPipeline.from_pretrained(model_id), torch_dtype=torch.bfloat16) # loading directly in bf16
pipeline.load_lora_weights(adapter_id)
prompt = "This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine's steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine's drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors."
## Optional: quantise the model to save on vram.
## Note: The model was not quantised during training, so it is not necessary to quantise it 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=3.0,
).images[0]
image.save("output.png", format="PNG")
```
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