---
license: other
base_model: "FLUX.1-dev"
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: 'bssprshps car interior objects, black background, vertically positioned, antenna'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_1_0.png
- text: 'bssprshps car interior objects, car dashboard cover, gray, car interior background, on top of the dashboard, side view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_2_0.png
- text: 'bssprshps car interior objects, windshield phone mount, on top of a silky cloth, side view, silky cloth background'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_3_0.png
- text: 'bssprshps car interior objects, windshield phone mount, car interior background, sticking on the windshield, isometric view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_4_0.png
- text: 'snwypnswhtlbs dog, front view, sitting position, tongue is out, collar on its neck and leash is lifted up, grass field on the back, sitting on a cement ground'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_5_0.png
- text: 'snwypnswhtlbs dog, front view, out-of-focus background, laying on a white blanket, red ribbon on its neck'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_6_0.png
- text: 'snwypnswhtlbs dog, laying on the water, tongue is out, out-of-focus background, pond background, facing on the right side'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_7_0.png
- text: 'snwypnswhtlbs dog, running in the water, out-of-focus background, lake background, running to the left, side view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_8_0.png
- text: 'bssprshps cooler, brown and black, white background, front view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_9_0.png
- text: 'bssprshps cooler, opened, red, front view, garden background, on the ground, filled with drinks and fruits and bread'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_10_0.png
- text: 'bssprshps cooler, front view, boat on water background, on top of a boat, light skinned person closing the box'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_11_0.png
- text: 'bssprshps cooler, turquoise, opened, isometric view, white background'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_12_0.png
- text: 'dptyq perfume, white background, next to a red coral and oval glass, corail oscuro scent, product is laying'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_13_0.png
- text: 'dptyq perfume, white background, product is laying, bottle cap is next to the product, top view, doson scent, perfume bottle is open, oval bottle and cylinder-shaped cap'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_14_0.png
- text: 'dptyq perfume, oval bottle and cylinder-shaped cap, product is laying, leau papier scent, on the floor, next to a writing materials'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_15_0.png
- text: 'dptyq perfume, oval bottle and cylinder-shaped cap, leau papier scent, product is laying, top view, next to the product branding'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_16_0.png
- text: 'bssprshps hat, orange, white background, isometric view, corduroy'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_17_0.png
- text: 'bssprshps hat, brown, on top of the couch, front view, navy blue couch, text only logo'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_18_0.png
- text: 'bssprshps hat, sky blue, black background, isometric view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_19_0.png
- text: 'bssprshps hat, camo brown and green, black background, isometric view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_20_0.png
- text: 'dptyq perfume set, white background, cylinder-shaped bottles, front view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_21_0.png
- text: 'dptyq perfume set, white background, cylinder-shaped bottles, front view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_22_0.png
- text: 'dptyq perfume set, front view, on the packaging box, next to the packaging cover, black background'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_23_0.png
- text: 'dptyq perfume set, white background, front view, on the packaging box, next to the packaging cover'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_24_0.png
- text: 'dptyq car diffuser, white background, amber scent, back view, next to the product packaging'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_25_0.png
- text: 'dptyq car diffuser, white background, roses scent, back view, next to the product packaging'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_26_0.png
- text: 'dptyq car diffuser, white background, back view'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_27_0.png
- text: 'dptyq car diffuser, white background, back view, ginger scent, next to the product packaging'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_28_0.png
- text: 'bssprshps head net, worn by a tan-skinned woman, worn by a dark-skinned man, out-of-focus background, front view, taking a selfie, wearing a camo hat and a teal and gray striped shirt, wearing a woven hat and a flannel shirt'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_29_0.png
- text: 'bssprshps head net, worn by a mannequin head, side view, white background, wearing a white hat'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_30_0.png
- text: 'bssprshps head net, worn by a light-skinned man, side view, white background, wearing a black baseball cap and a white shirt'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_31_0.png
- text: 'bssprshps head net, out-of-focus background, worn by a light-skinned woman, side view, green, wearing a knitted hat, glasses, and a dark shirt'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_32_0.png
- text: 'a photo of a daisy'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_33_0.png
---

# y

This is a LyCORIS adapter derived from [FLUX.1-dev](https://huggingface.co/FLUX.1-dev).


The main validation prompt used during training was:
```
a photo of a daisy
```


## Validation settings
- CFG: `3.5`
- CFG Rescale: `0.0`
- Steps: `20`
- Sampler: `FlowMatchEulerDiscreteScheduler`
- Seed: `69`
- 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: 30
- Training steps: 3000
- Learning rate: 0.0001
  - Learning rate schedule: constant
  - Warmup steps: 0
- Max grad norm: 2.0
- Effective batch size: 8
  - Micro-batch size: 2
  - Gradient accumulation steps: 1
  - Number of GPUs: 4
- Gradient checkpointing: True
- Prediction type: flow-matching (extra parameters=['shift=3', 'flux_guidance_mode=constant', 'flux_guidance_value=1.0', 'flow_matching_loss=compatible'])
- Optimizer: optimi-stableadamwweight_decay=1e-3
- Trainable parameter precision: Pure BF16
- Caption dropout probability: 5.0%

### LyCORIS Config:
```json
{
    "algo": "lokr",
    "multiplier": 1,
    "linear_dim": 1000000,
    "linear_alpha": 1,
    "factor": 12,
    "init_lokr_norm": 0.001,
    "apply_preset": {
        "target_module": [
            "FluxTransformerBlock",
            "FluxSingleTransformerBlock"
        ],
        "module_algo_map": {
            "Attention": {
                "factor": 12
            },
            "FeedForward": {
                "factor": 6
            }
        }
    }
}
```

## Datasets

### dptyqxbssprshps_flat-512
- Repeats: 0
- Total number of images: ~216
- Total number of aspect buckets: 2
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### dptyqxbssprshps_flat-768
- Repeats: 0
- Total number of images: ~180
- Total number of aspect buckets: 10
- Resolution: 0.589824 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### dptyqxbssprshps_flat-1024
- Repeats: 1
- Total number of images: ~152
- Total number of aspect buckets: 11
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No


## Inference


```python
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 = 'FLUX.1-dev'
adapter_repo_id = 'playerzer0x/y'
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 = "a photo of a daisy"


## 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(69),
    width=1024,
    height=1024,
    guidance_scale=3.5,
).images[0]
image.save("output.png", format="PNG")
```