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andre_68386_81501/flux_dev_XRAYv2/config.yaml

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+config:
+ name: flux_dev_XRAYv2
+ process:
+ - datasets:
+ - cache_latents_to_disk: true
+ caption_dropout_rate: 0.2
+ caption_ext: txt
+ folder_path: /root/lorahub/flux_dev_XRAYv2/dataset
+ resolution:
+ - 512
+ - 768
+ - 1024
+ shuffle_tokens: false
+ token_dropout_rate: 0.01
+ device: cuda:0
+ model:
+ is_flux: true
+ name_or_path: black-forest-labs/FLUX.1-dev
+ quantize: true
+ text_encoder_bits: 8
+ network:
+ linear: 42
+ linear_alpha: 42
+ transformer_only: true
+ type: lora
+ performance_log_every: 500
+ sample:
+ height: 768
+ neg: ''
+ prompts:
+ - a skeleton wearing a hat playing poker at a table [trigger]
+ - old computers standing on a table [trigger]
+ - black and white image of a young woman [trigger]
+ - deep sea creature [trigger]
+ - monochrome, an old car parked in front of a suburb house [trigger]
+ - monochrome, image of trees and surreal shaped branches [trigger]
+ sample_every: 500
+ sample_steps: 25
+ sampler: flowmatch
+ seed: 42
+ walk_seed: true
+ width: 1182
+ save:
+ dtype: float16
+ max_step_saves_to_keep: 3
+ save_every: 500
+ save_format: diffusers
+ train:
+ batch_size: 1
+ dtype: bf16
+ ema_config:
+ ema_decay: 0.99
+ use_ema: true
+ gradient_accumulation_steps: 1
+ gradient_checkpointing: true
+ linear_timesteps: true
+ loss_type: mse
+ lr: 1.0
+ noise_scheduler: flowmatch
+ optimizer: prodigy
+ reg_weight: 1.0
+ steps: 3000
+ target_noise_multiplier: 1.0
+ train_text_encoder: false
+ train_unet: true
+ training_folder: /root/lorahub
+ trigger_word: XRAY,x-ray
+ type: sd_trainer
+job: extension
+meta:
+ description: Trained on high resolution X-Ray images of humans, reptiles, fish and
+ technology.

andre_68386_81501/flux_dev_XRAYv2/flux_dev_XRAYv2.safetensors

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