| --- |
| 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 |
| - lycoris |
| inference: true |
| widget: |
| - text: 'unconditional (blank prompt)' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_0_0.png |
| - text: 'In the style of a Raphael oil painting, Three figures in red and white religious attire, with one seated at a table holding a magnifying glass, and two standing figures behind. The table is covered with a red cloth and holds an open book and a silver bell. Dark background and muted color palette.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_1_0.png |
| - text: 'In the style of a Raphael oil painting, A knight on a white horse is spearing a dragon lying on the ground. The knight wears armor and a blue cape, while a woman in a red dress stands in the background beside a rock formation. The setting includes tall trees and a distant cityscape.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_2_0.png |
| - text: 'In the style of a Raphael oil painting, A bearded man wearing a black robe and cap sits at a table holding papers in one hand. An apple rests on the table alongside a book with a ring visible on his finger. The background is plain and neutral.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_3_0.png |
| - text: 'In the style of a Raphael oil painting, A seated figure in a blue robe and red dress holds a book, surrounded by two young, unclothed children in a natural setting with trees and mountains in the background. One child holds a bird while the other reaches out towards it. The setting includes a rock and a grassy landscape.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_4_0.png |
| - text: 'In the style of a Raphael oil painting, A scholar-alchemist in flowing robes stands amid glass vessels and astronomical instruments, while light streams through a Gothic window. A mechanical armillary sphere sits prominently on a wooden table, while an assistant in the background tends to a burning crucible.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_5_0.png |
| - text: 'In the style of a Raphael oil painting, Neptune rises from turbulent waters on the steps of Venice''s St. Mark''s Basilica, offering a golden ring to a figure representing the Maritime Republic. Merchants in Renaissance dress observe from gondolas, while angels hold scrolls of maritime law above.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_6_0.png |
| - text: 'In the style of a Raphael oil painting, Aristotle and Plato walk through a Renaissance medicinal garden, discussing a dissected flower. Young apprentices sketch botanical specimens nearby, while in the background, monks tend to rows of healing herbs beneath a pergola covered in grape vines.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_7_0.png |
| - text: 'In the style of a Raphael oil painting, Angels and scholars share a vast library with soaring Renaissance architecture, where celestial maps float in mid-air. Some angels point to globes showing undiscovered continents, while others transcribe from books bound in supernatural light. A telescope made of gold and ivory points through an open dome to the stars.' |
| parameters: |
| negative_prompt: 'blurry, cropped, ugly' |
| output: |
| url: ./assets/image_8_0.png |
| --- |
| |
| # Flux-Raphael-LoRA |
|
|
| This is a LyCORIS adapter derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev). |
|
|
|
|
| No validation prompt was used during training. |
|
|
| None |
|
|
|
|
|
|
| ## Validation settings |
| - CFG: `3.0` |
| - CFG Rescale: `0.0` |
| - Steps: `20` |
| - Sampler: `FlowMatchEulerDiscreteScheduler` |
| - Seed: `42` |
| - Resolution: `1024x1280` |
| - 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: 0 |
| - Training steps: 200 |
| - Learning rate: 0.0006 |
| - Learning rate schedule: polynomial |
| - Warmup steps: 100 |
| - Max grad norm: 2.0 |
| - Effective batch size: 4 |
| - Micro-batch size: 2 |
| - Gradient accumulation steps: 2 |
| - Number of GPUs: 1 |
| - 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: adamw_bf16 |
| - Trainable parameter precision: Pure BF16 |
| - Caption dropout probability: 10.0% |
| |
| - SageAttention: Enabled inference |
| ### LyCORIS Config: |
| ```json |
| { |
| "algo": "lokr", |
| "multiplier": 1.0, |
| "linear_dim": 10000, |
| "linear_alpha": 1, |
| "factor": 16, |
| "apply_preset": { |
| "target_module": [ |
| "Attention", |
| "FeedForward" |
| ], |
| "module_algo_map": { |
| "Attention": { |
| "factor": 16 |
| }, |
| "FeedForward": { |
| "factor": 8 |
| } |
| } |
| } |
| } |
| ``` |
| |
| ## Datasets |
|
|
| ### raphael-512 |
| - Repeats: 15 |
| - Total number of images: 28 |
| - Total number of aspect buckets: 6 |
| - Resolution: 0.262144 megapixels |
| - Cropped: False |
| - Crop style: None |
| - Crop aspect: None |
| - Used for regularisation data: No |
| ### raphael-768 |
| - Repeats: 12 |
| - Total number of images: 28 |
| - Total number of aspect buckets: 9 |
| - Resolution: 0.589824 megapixels |
| - Cropped: False |
| - Crop style: None |
| - Crop aspect: None |
| - Used for regularisation data: No |
| ### raphael-1024 |
| - Repeats: 8 |
| - Total number of images: 28 |
| - Total number of aspect buckets: 3 |
| - Resolution: 1.048576 megapixels |
| - Cropped: False |
| - Crop style: None |
| - Crop aspect: None |
| - Used for regularisation data: No |
| ### raphael-crops-512 |
| - Repeats: 6 |
| - 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 |
| ### raphael-crops-1024 |
| - Repeats: 4 |
| - 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 |
| ### raphael-crops-512-from-1024 |
| - Repeats: 6 |
| - 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 |
| ### raphael-crops-512-from-1536 |
| - Repeats: 4 |
| - 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 |
|
|
|
|
| ## 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 = 'black-forest-labs/FLUX.1-dev' |
| adapter_repo_id = 'davidrd123/Flux-Raphael-LoRA' |
| 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 astronaut is riding a horse through the jungles of Thailand." |
| |
| |
| ## 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(42), |
| width=1024, |
| height=1280, |
| guidance_scale=3.0, |
| ).images[0] |
| image.save("output.png", format="PNG") |
| ``` |
|
|
|
|
|
|
| ## Exponential Moving Average (EMA) |
|
|
| SimpleTuner generates a safetensors variant of the EMA weights and a pt file. |
|
|
| The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning. |
|
|
| The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights. |
|
|
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|
