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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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+ - safe-for-work
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+ - lora
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+ - template:sd-lora
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+ - standard
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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 girl in light blue sits at the bar counter, holding an ice-cold wine glass and drinking alone on top of the Eiffel Tower, with a night view outside the window.. It features a close-up shot of her sitting by herself. She has long hair, wears glasses, faces away from the camera, and is wearing white shoes, black pants, a gray jacket, and a green scarf. with bright colors and a Paris night background featuring the Eiffel Tower. The composition is elegant, with the woman sitting on a high stool'
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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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+ ---
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+
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+ # jazzy-st-2211
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+
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+ This is a standard PEFT LoRA 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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+ A girl in light blue sits at the bar counter, holding an ice-cold wine glass and drinking alone on top of the Eiffel Tower, with a night view outside the window.. It features a close-up shot of her sitting by herself. She has long hair, wears glasses, faces away from the camera, and is wearing white shoes, black pants, a gray jacket, and a green scarf. with bright colors and a Paris night background featuring the Eiffel Tower. The composition is elegant, with the woman sitting on a high stool
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+ ```
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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: `20`
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+ - Sampler: `FlowMatchEulerDiscreteScheduler`
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+ - Seed: `42`
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+ - Resolution: `1080x1920`
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+ - Skip-layer guidance:
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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: 0.0004
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+ - Learning rate schedule: polynomial
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+ - Warmup steps: 100
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+ - Max grad norm: 2.0
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+ - Effective batch size: 1
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+ - Micro-batch size: 1
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+ - Gradient accumulation steps: 1
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+ - Number of GPUs: 1
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+ - Gradient checkpointing: True
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+ - Prediction type: flow-matching (extra parameters=['shift=3', 'flux_guidance_mode=constant', 'flux_guidance_value=1.0', 'flow_matching_loss=compatible', 'flux_lora_target=all'])
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+ - Optimizer: adamw_bf16
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+ - Trainable parameter precision: Pure BF16
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+ - Caption dropout probability: 10.0%
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+
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+ - LoRA Rank: 32
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+ - LoRA Alpha: 32.0
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+ - LoRA Dropout: 0.1
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+ - LoRA initialisation style: default
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+
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+
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+ ## Datasets
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+
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+ ### jazzy-512
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+ - Repeats: 10
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+ - Total number of images: 23
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+ - Total number of aspect buckets: 2
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+ - Resolution: 0.262144 megapixels
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+ - Cropped: False
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+ - Crop style: None
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+ - Crop aspect: None
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+ - Used for regularisation data: No
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+ ### jazzy-768
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+ - Repeats: 10
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+ - Total number of images: 23
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+ - Total number of aspect buckets: 1
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+ - Resolution: 0.589824 megapixels
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+ - Cropped: False
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+ - Crop style: None
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+ - Crop aspect: None
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+ - Used for regularisation data: No
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+ ### jazzy-1024
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+ - Repeats: 10
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+ - Total number of images: 23
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+ - Total number of aspect buckets: 1
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+ - Resolution: 1.048576 megapixels
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+ - Cropped: False
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+ - Crop style: None
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+ - Crop aspect: None
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+ - Used for regularisation data: No
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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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+
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+ model_id = 'black-forest-labs/FLUX.1-dev'
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+ adapter_id = 'linhqyy/jazzy-st-2211'
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+ pipeline = DiffusionPipeline.from_pretrained(model_id), torch_dtype=torch.bfloat16) # loading directly in bf16
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+ pipeline.load_lora_weights(adapter_id)
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+
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+ prompt = "A girl in light blue sits at the bar counter, holding an ice-cold wine glass and drinking alone on top of the Eiffel Tower, with a night view outside the window.. It features a close-up shot of her sitting by herself. She has long hair, wears glasses, faces away from the camera, and is wearing white shoes, black pants, a gray jacket, and a green scarf. with bright colors and a Paris night background featuring the Eiffel Tower. The composition is elegant, with the woman sitting on a high stool"
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+
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+
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+ ## Optional: quantise the model to save on vram.
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+ ## Note: The model was not quantised during training, so it is not necessary to quantise it during inference time.
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+ #from optimum.quanto import quantize, freeze, qint8
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+ #quantize(pipeline.transformer, weights=qint8)
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+ #freeze(pipeline.transformer)
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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') # the pipeline is already in its target precision level
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+ image = pipeline(
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+ prompt=prompt,
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+ num_inference_steps=20,
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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(42),
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+ width=1080,
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+ height=1920,
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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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+