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- dataset.toml +14 -0
- sample/signature-02e-adj_000450_00_20241224172747.png +0 -0
- sample/signature-02e-adj_000900_00_20241224174602.png +0 -0
- sample/signature-02e-adj_001350_00_20241224180409.png +0 -0
- sample/signature-02e-adj_001800_00_20241224182217.png +0 -0
- sample/signature-02e-adj_002250_00_20241224184020.png +0 -0
- sample/signature-02e-adj_002700_00_20241224185746.png +0 -0
- sample/signature-02e-adj_003150_00_20241224191414.png +0 -0
- sample/signature-02e-adj_003600_00_20241224193225.png +0 -0
- sample/signature-02e-adj_004050_00_20241224195034.png +0 -0
- sample/signature-02e-adj_004500_00_20241224200840.png +0 -0
- sample/signature-02e-adj_004950_00_20241224202646.png +0 -0
- sample_prompts.txt +1 -0
- signature-02e-adj-000004.safetensors +3 -0
- signature-02e-adj-000008.safetensors +3 -0
- signature-02e-adj-000012.safetensors +3 -0
- signature-02e-adj.safetensors +3 -0
- train.bat +34 -0
README.md
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---
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tags:
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- text-to-image
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- flux
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- lora
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- diffusers
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- template:sd-lora
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- fluxgym
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widget:
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- output:
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url: sample/signature-02e-adj_004950_00_20241224202646.png
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text: signature-02e generate a black signature on white background for
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base_model: black-forest-labs/FLUX.1-schnell
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instance_prompt: signature-02e generate a black signature on white background for
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license: apache-2.0
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---
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# signature-02e-adj
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A Flux LoRA trained on a local computer with [Fluxgym](https://github.com/cocktailpeanut/fluxgym)
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<Gallery />
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## Trigger words
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You should use `signature-02e generate a black signature on white background for` to trigger the image generation.
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## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
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Weights for this model are available in Safetensors format.
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dataset.toml
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[general]
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shuffle_caption = false
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caption_extension = '.txt'
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keep_tokens = 1
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[[datasets]]
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resolution = 512
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batch_size = 1
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keep_tokens = 1
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[[datasets.subsets]]
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image_dir = 'C:\pinokio\api\fluxgym\datasets\signature-02e-adj'
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class_tokens = 'signature-02e generate a black signature on white background for'
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num_repeats = 13
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sample/signature-02e-adj_000450_00_20241224172747.png
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sample_prompts.txt
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signature-02e generate a black signature on white background for
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signature-02e-adj-000004.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec2d5889b2e2451dde2ca41d93ddfd540b0982a7d64250747b7c86bdb50f463c
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size 39763832
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signature-02e-adj-000008.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4a62f18b0d949d7444da1a7697da46a4dc2c96e02354a9d8a2c21cf7d2de8554
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size 39763832
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signature-02e-adj-000012.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7aebf0640b53611e37c15b41eeba4a1ef9bda7cd44b606ae05adbcd2f5568f45
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size 39763832
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signature-02e-adj.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c25a19531f7be11afaec9e15ecb1a019824379ca2cab516fafd44caaa54d0b6e
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size 39763832
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train.bat
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accelerate launch ^
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--mixed_precision bf16 ^
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--num_cpu_threads_per_process 1 ^
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sd-scripts/flux_train_network.py ^
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--pretrained_model_name_or_path "C:\pinokio\api\fluxgym\models\unet\flux1-schnell.safetensors" ^
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--clip_l "C:\pinokio\api\fluxgym\models\clip\clip_l.safetensors" ^
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--t5xxl "C:\pinokio\api\fluxgym\models\clip\t5xxl_fp16.safetensors" ^
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--ae "C:\pinokio\api\fluxgym\models\vae\ae.sft" ^
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--cache_latents_to_disk ^
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--save_model_as safetensors ^
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--sdpa --persistent_data_loader_workers ^
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--max_data_loader_n_workers 2 ^
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--seed 42 ^
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--gradient_checkpointing ^
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--mixed_precision bf16 ^
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--save_precision bf16 ^
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--network_module networks.lora_flux ^
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--network_dim 4 ^
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--optimizer_type adamw8bit ^--sample_prompts="C:\pinokio\api\fluxgym\outputs\signature-02e-adj\sample_prompts.txt" --sample_every_n_steps="450" ^
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--learning_rate 8e-4 ^
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--cache_text_encoder_outputs ^
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--cache_text_encoder_outputs_to_disk ^
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--fp8_base ^
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--highvram ^
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--max_train_epochs 16 ^
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--save_every_n_epochs 4 ^
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--dataset_config "C:\pinokio\api\fluxgym\outputs\signature-02e-adj\dataset.toml" ^
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--output_dir "C:\pinokio\api\fluxgym\outputs\signature-02e-adj" ^
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--output_name signature-02e-adj ^
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--timestep_sampling shift ^
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--discrete_flow_shift 3.1582 ^
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--model_prediction_type raw ^
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--guidance_scale 1 ^
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--loss_type l2 ^
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