--- license: other base_model: "black-forest-labs/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: 'gh logo, on four cans, black background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_1_0.png - text: 'gh logo, green background, on a bottle and a can' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_2_0.png - text: 'gh logo, on a bottle and 4 cans, white background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_3_0.png - text: 'gh logo, on a bottle and two cans, red orange background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_4_0.png - text: 'gh cans, yellow background, brown red can, served with other drinks' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_5_0.png - text: 'gh cans, white background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_6_0.png - text: 'gh cans, in a bucket of ice, white background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_7_0.png - text: 'gh cans, being held, out of focus background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_8_0.png - text: 'dct desert rally racing background, driving a Ducati bike, out of focus shrubbery' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_9_0.png - text: 'dct desert rally racing background, driving a Ducati bike, splashing water' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_10_0.png - text: 'dct desert rally racing background, driving a Ducati bike, rider in a white motocross outfit, dust cloud' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_11_0.png - text: 'dct desert rally racing background, driving a Ducati bike, view of a lake with shrubs and trees in the background, other riders and spectators' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_12_0.png - text: 'anytylrjy woman, wearing a neckless and an opaque brown dress standing on the red carpet, hair done up, front view' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_13_0.png - text: 'anytylrjy woman, putting on lipstick in front of a mirror, wearing a flowing white dress or bathrobe, looking in multiple mirrors, makeup on table' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_14_0.png - text: 'anytylrjy woman, holding a makeup kit, staring directly at camera, brown background, wearing a ring and eggshell dress' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_15_0.png - text: 'anytylrjy woman, wearing an elegant emerald green dress, wearing earrings and a necklace, white background' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_16_0.png - text: 'mrtnprr style' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_17_0.png - text: 'mrtnprr style' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_18_0.png - text: 'mrtnprr style' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_19_0.png - text: 'mrtnprr style' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_20_0.png - text: 'a photo of a daisy' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_21_0.png --- # growwithdaisy/ghxdct_style_focus_20241113_125207 This is a LyCORIS adapter 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: ``` a photo of a daisy ``` ## Validation settings - CFG: `3.5` - CFG Rescale: `0.0` - Steps: `20` - Sampler: `None` - Seed: `69` - 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: The text encoder **was not** trained. You may reuse the base model text encoder for inference. ## Training settings - Training epochs: 50 - Training steps: 4500 - Learning rate: 5e-06 - Max grad norm: 2.0 - Effective batch size: 8 - Micro-batch size: 1 - Gradient accumulation steps: 1 - Number of GPUs: 8 - Prediction type: flow-matching (extra parameters=['shift=3', 'flux_guidance_value=1.0']) - Rescaled betas zero SNR: False - Optimizer: optimi-stableadamwweight_decay=1e-3 - Precision: Pure BF16 - Quantised: No - Xformers: Not used - LyCORIS Config: ```json { "algo": "lokr", "multiplier": 1, "linear_dim": 1000000, "linear_alpha": 1, "factor": 16, "init_lokr_norm": 0.001, "apply_preset": { "target_module": [ "FluxTransformerBlock", "FluxSingleTransformerBlock" ], "module_algo_map": { "Attention": { "factor": 16 }, "FeedForward": { "factor": 8 } } } } ``` ## Datasets ### gh_logo-512 - Repeats: 0 - Total number of images: ~32 - Total number of aspect buckets: 4 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### gh_cans-512 - Repeats: 0 - Total number of images: ~56 - Total number of aspect buckets: 6 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### gh_cans-768 - Repeats: 0 - Total number of images: ~40 - Total number of aspect buckets: 5 - Resolution: 0.589824 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### gh_cans-1024 - Repeats: 0 - Total number of images: ~16 - Total number of aspect buckets: 2 - Resolution: 1.048576 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### dct_desert_rally_racing_background-512 - Repeats: 0 - Total number of images: ~56 - Total number of aspect buckets: 5 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### dct_desert_rally_racing_background-768 - Repeats: 0 - Total number of images: ~56 - Total number of aspect buckets: 5 - Resolution: 0.589824 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### dct_desert_rally_racing_background-1024 - Repeats: 0 - Total number of images: ~48 - Total number of aspect buckets: 4 - Resolution: 1.048576 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### anytylrjy_woman-512 - Repeats: 0 - Total number of images: ~64 - Total number of aspect buckets: 7 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### anytylrjy_woman-768 - Repeats: 0 - Total number of images: ~64 - Total number of aspect buckets: 7 - Resolution: 0.589824 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### anytylrjy_woman-1024 - Repeats: 0 - Total number of images: ~72 - Total number of aspect buckets: 8 - Resolution: 1.048576 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### mrtnprr_style-512 - Repeats: 1 - Total number of images: ~48 - Total number of aspect buckets: 6 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### mrtnprr_style-768 - Repeats: 1 - Total number of images: ~40 - Total number of aspect buckets: 5 - Resolution: 0.589824 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### mrtnprr_style-1024 - Repeats: 1 - Total number of images: ~16 - Total number of aspect buckets: 2 - 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 = 'black-forest-labs/FLUX.1-dev' adapter_repo_id = 'playerzer0x/growwithdaisy/ghxdct_style_focus_20241113_125207' 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(1641421826), width=1024, height=1024, guidance_scale=3.5, ).images[0] image.save("output.png", format="PNG") ```