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+ ---
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+ license: other
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+ base_model: "black-forest-labs/FLUX.1-dev"
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+ tags:
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+ - flux
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+ - flux-diffusers
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+ - text-to-image
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+ - diffusers
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+ - simpletuner
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+ - lora
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+ - template:sd-lora
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+ inference: true
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+ widget:
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+ - text: 'unconditional (blank prompt)'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_0_0.png
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+ - text: 'a silly psychedelic style desk telephone'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_1_0.png
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+ - text: 'a psychedelic style pikachu'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_2_0.png
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+ - text: 'psychedelic style batman toy'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_3_0.png
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+ - text: 'an overhead shot of a race track shaped like psychedelic'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_4_0.png
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+ - text: 'a woman is wearing a psychedelic necklace'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_5_0.png
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+ - text: 'a book with the psychedelic character on the front cover'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_6_0.png
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+ - text: 'psychedelic trip to the grand canyon'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_7_0.png
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+ - text: 'a psychedelic version of sandy shores, the instagram model hanging out on the beach'
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+ parameters:
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+ negative_prompt: 'blurry, cropped, ugly'
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+ output:
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+ url: ./assets/image_8_0.png
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+ ---
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+
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+ # flux-lokr-psychedelic
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+
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+ This is a LyCORIS adapter derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev).
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+
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+
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+ The main validation prompt used during training was:
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+
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+
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+
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+ ```
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+ a psychedelic version of sandy shores, the instagram model hanging out on the beach
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+ ```
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+
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+ ## Validation settings
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+ - CFG: `3.0`
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+ - CFG Rescale: `0.0`
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+ - Steps: `25`
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+ - Sampler: `None`
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+ - Seed: `42`
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+ - Resolution: `1024x1024`
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+
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+ Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
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+
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+ You can find some example images in the following gallery:
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+
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+
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+ <Gallery />
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+
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+ The text encoder **was not** trained.
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+ You may reuse the base model text encoder for inference.
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+
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+
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+ ## Training settings
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+
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+ - Training epochs: 0
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+ - Training steps: 500
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+ - Learning rate: 5e-05
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+ - Effective batch size: 2
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+ - Micro-batch size: 2
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+ - Gradient accumulation steps: 1
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+ - Number of GPUs: 1
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+ - Prediction type: flow-matching
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+ - Rescaled betas zero SNR: False
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+ - Optimizer: optimi-lion
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+ - Precision: bf16
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+ - Quantised: Yes: int8-quanto
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+ - Xformers: Not used
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+ - LyCORIS Config:
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+ ```json
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+ {
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+ "algo": "lokr",
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+ "multiplier": 1.0,
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+ "linear_dim": 10000,
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+ "linear_alpha": 1,
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+ "factor": 10,
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+ "apply_preset": {
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+ "target_module": [
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+ "Attention",
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+ "FeedForward"
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+ ],
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+ "module_algo_map": {
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+ "Attention": {
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+ "factor": 10
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+ },
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+ "FeedForward": {
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+ "factor": 6
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+ }
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+ }
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+ }
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+ }
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+ ```
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+
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+ ## Datasets
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+
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+ ### psychedelic
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+ - Repeats: 10
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+ - Total number of images: 33
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+ - Total number of aspect buckets: 1
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+ - Resolution: 1024 px
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+ - Cropped: True
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+ - Crop style: center
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+ - Crop aspect: square
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+ ### psychedelic-512
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+ - Repeats: 10
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+ - Total number of images: 42
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+ - Total number of aspect buckets: 1
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+ - Resolution: 512 px
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+ - Cropped: True
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+ - Crop style: center
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+ - Crop aspect: square
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+
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+
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+ ## Inference
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+
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+
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+ ```python
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+ import torch
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+ from diffusers import DiffusionPipeline
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+ from lycoris import create_lycoris_from_weights
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+
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+ model_id = 'black-forest-labs/FLUX.1-dev'
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+ adapter_id = 'pytorch_lora_weights.safetensors' # you will have to download this manually
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+ lora_scale = 1.0
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+ wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
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+ wrapper.merge_to()
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+
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+ prompt = "a psychedelic version of sandy shores, the instagram model hanging out on the beach"
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+
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+ pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
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+ image = pipeline(
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+ prompt=prompt,
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+ num_inference_steps=25,
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+ generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
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+ width=1024,
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+ height=1024,
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+ guidance_scale=3.0,
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+ ).images[0]
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+ image.save("output.png", format="PNG")
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+ ```
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+