--- 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 - standard inference: true widget: - text: 'unconditional (blank prompt)' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_0_0.png - text: 'This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine''s steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine''s drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors.' parameters: negative_prompt: 'blurry, cropped, ugly' output: url: ./assets/image_1_0.png --- # jazzy-st This is a standard PEFT LoRA 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: ``` This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine's steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine's drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors. ``` ## Validation settings - CFG: `3.0` - CFG Rescale: `0.0` - Steps: `20` - Sampler: `None` - Seed: `42` - 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: 4 - Training steps: 5000 - Learning rate: 0.0004 - Max grad norm: 2.0 - Effective batch size: 1 - Micro-batch size: 1 - Gradient accumulation steps: 1 - Number of GPUs: 1 - Prediction type: flow-matching (extra parameters=['shift=3', 'flux_guidance_value=1.0', 'flux_lora_target=all']) - Rescaled betas zero SNR: False - Optimizer: adamw_bf16 - Precision: Pure BF16 - Quantised: No - Xformers: Not used - LoRA Rank: 64 - LoRA Alpha: None - LoRA Dropout: 0.1 - LoRA initialisation style: default ## Datasets ### jazzy-512 - Repeats: 10 - Total number of images: 28 - Total number of aspect buckets: 1 - Resolution: 0.262144 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### jazzy-1024 - Repeats: 10 - Total number of images: 28 - Total number of aspect buckets: 1 - Resolution: 1.048576 megapixels - Cropped: False - Crop style: None - Crop aspect: None - Used for regularisation data: No ### jazzy-512-crop - Repeats: 10 - 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 ### jazzy-1024-crop - Repeats: 10 - 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 ## Inference ```python import torch from diffusers import DiffusionPipeline model_id = 'black-forest-labs/FLUX.1-dev' adapter_id = 'linhqyy/jazzy-st' pipeline = DiffusionPipeline.from_pretrained(model_id), torch_dtype=torch.bfloat16) # loading directly in bf16 pipeline.load_lora_weights(adapter_id) prompt = "This is a digital drawing in a warm, pastel color palette, featuring a close-up view of a vintage-style coffee machine. The coffee machine is cream-colored with a golden trim and has a classic, retro design. It includes a large, circular dial on the right side, which is blue with a red pointer, indicating settings or temperature control. The coffee machine's steam wand is positioned in the center, with a dark green handle and a white steam nozzle. The steam wand is currently in use, evidenced by a small amount of coffee being extracted into a white ceramic cup placed directly below. The coffee machine's drip tray is visible beneath the cup, with a rectangular opening for the coffee to collect. The background is soft and muted, with warm tones that blend into the image, giving it a cozy and inviting atmosphere. The overall style of the drawing is reminiscent of mid-century modern design, with smooth, clean lines and a focus on warm, comforting colors." ## 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=3.0, ).images[0] image.save("output.png", format="PNG") ```