Instructions to use VHKE/boymod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/boymod with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("VHKE/boymod") prompt = "boymod" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- README.md +33 -0
- boymod-000004.safetensors +3 -0
- boymod-000008.safetensors +3 -0
- boymod-000012.safetensors +3 -0
- boymod.safetensors +3 -0
- dataset.toml +14 -0
- sample/boymod_000500_00_20250713213623.png +3 -0
- sample/boymod_001000_00_20250713214612.png +3 -0
- sample_prompts.txt +1 -0
- train.bat +37 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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sample/boymod_000500_00_20250713213623.png filter=lfs diff=lfs merge=lfs -text
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sample/boymod_001000_00_20250713214612.png filter=lfs diff=lfs merge=lfs -text
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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/boymod_001000_00_20250713214612.png
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text: boymod
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: boymod
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
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---
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# boymod
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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 `boymod` 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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boymod-000004.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8602bc6e5a9c8c18483697a75a15e5895c936e528ba6a4b2f7d65da81b14f2a5
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size 39759240
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boymod-000008.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:51fe708320622b39d67716c0062acc3c542516fde8f7324537f8b088a64bcda5
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size 39759240
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boymod-000012.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fb71d01fe3a8be1c5d43e0572ebdc8cae9ceaec4fe7c012f654442928ce6e009
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size 39759240
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boymod.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c1178325aa9fb080f1055a89065f4217798dfd9f00d7d61a32c980c7216443ec
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size 39759240
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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:\pinokioFOLDER\api\fluxgym.git\datasets\boymod'
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class_tokens = 'boymod'
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num_repeats = 10
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sample/boymod_000500_00_20250713213623.png
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Git LFS Details
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sample/boymod_001000_00_20250713214612.png
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Git LFS Details
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sample_prompts.txt
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boymod
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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:\pinokioFOLDER\api\fluxgym.git\models\unet\flux1-dev.sft" ^
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--clip_l "C:\pinokioFOLDER\api\fluxgym.git\models\clip\clip_l.safetensors" ^
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--t5xxl "C:\pinokioFOLDER\api\fluxgym.git\models\clip\t5xxl_fp16.safetensors" ^
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--ae "C:\pinokioFOLDER\api\fluxgym.git\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 adafactor ^
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--optimizer_args "relative_step=False" "scale_parameter=False" "warmup_init=False" ^
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--lr_scheduler constant_with_warmup ^
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--max_grad_norm 0.0 ^--sample_prompts="C:\pinokioFOLDER\api\fluxgym.git\outputs\boymod\sample_prompts.txt" --sample_every_n_steps="500" ^
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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:\pinokioFOLDER\api\fluxgym.git\outputs\boymod\dataset.toml" ^
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--output_dir "C:\pinokioFOLDER\api\fluxgym.git\outputs\boymod" ^
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--output_name boymod ^
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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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