Instructions to use AiTools2/Aurvena01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiTools2/Aurvena01 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("AiTools2/Aurvena01") prompt = "Aurvena01" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload folder using huggingface_hub
Browse files- .gitattributes +25 -0
- README.md +33 -0
- aurvena-000004.safetensors +3 -0
- aurvena-000008.safetensors +3 -0
- aurvena-000012.safetensors +3 -0
- aurvena-000016.safetensors +3 -0
- aurvena-000020.safetensors +3 -0
- aurvena.safetensors +3 -0
- dataset.toml +14 -0
- sample/aurvena_000200_00_20250308105943.png +3 -0
- sample/aurvena_000400_00_20250308110947.png +3 -0
- sample/aurvena_000600_00_20250308111951.png +3 -0
- sample/aurvena_000800_00_20250308112954.png +3 -0
- sample/aurvena_001000_00_20250308113958.png +3 -0
- sample/aurvena_001200_00_20250308115001.png +3 -0
- sample/aurvena_001400_00_20250308120007.png +3 -0
- sample/aurvena_001600_00_20250308121011.png +3 -0
- sample/aurvena_001800_00_20250308122015.png +3 -0
- sample/aurvena_002000_00_20250308123020.png +3 -0
- sample/aurvena_002200_00_20250308124024.png +3 -0
- sample/aurvena_002400_00_20250308125028.png +3 -0
- sample/aurvena_002600_00_20250308130032.png +3 -0
- sample/aurvena_002800_00_20250308131035.png +3 -0
- sample/aurvena_003000_00_20250308132039.png +3 -0
- sample/aurvena_003200_00_20250308133042.png +3 -0
- sample/aurvena_003400_00_20250308134045.png +3 -0
- sample/aurvena_003600_00_20250308135048.png +3 -0
- sample/aurvena_003800_00_20250308140052.png +3 -0
- sample/aurvena_004000_00_20250308141054.png +3 -0
- sample/aurvena_004200_00_20250308142058.png +3 -0
- sample/aurvena_004400_00_20250308143102.png +3 -0
- sample/aurvena_004600_00_20250308144105.png +3 -0
- sample/aurvena_004800_00_20250308145108.png +3 -0
- sample/aurvena_005000_00_20250308150113.png +3 -0
- sample_prompts.txt +1 -0
- train.sh +34 -0
.gitattributes
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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/aurvena_005000_00_20250308150113.png
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text: Aurvena01
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: Aurvena01
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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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# Aurvena
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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 `Aurvena01` 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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aurvena-000004.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a643b92a18366bff786e021d29300494c1c865741b6fe8fc0e6ce76557d0b2b
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size 39764920
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oid sha256:8d9a6e23aa1eb6ca7a0618fb83d0044498b982ad1237a975f2b08edb740cb6bc
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size 39764920
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oid sha256:64ff342d560960a623159738e678a3dc8c5a4a69bfc222590b0b62a55d8f33a6
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version https://git-lfs.github.com/spec/v1
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oid sha256:beece1634c18183bd04fb1d2a08e359640b0d2d35d7f8cc685c0d7ff40b27763
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oid sha256:62e72294e828760c3886495c00b1a4cfe3e585cd3b9da7129d5ddca53555b941
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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 = 1024
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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 = '/app/fluxgym/datasets/aurvena'
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class_tokens = 'Aurvena01'
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num_repeats = 10
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sample_prompts.txt
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Aurvena01
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train.sh
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accelerate launch \
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| 2 |
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--mixed_precision bf16 \
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| 3 |
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--num_cpu_threads_per_process 1 \
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| 4 |
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sd-scripts/flux_train_network.py \
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| 5 |
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--pretrained_model_name_or_path "/app/fluxgym/models/unet/flux1-dev.sft" \
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| 6 |
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--clip_l "/app/fluxgym/models/clip/clip_l.safetensors" \
|
| 7 |
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--t5xxl "/app/fluxgym/models/clip/t5xxl_fp16.safetensors" \
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| 8 |
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--ae "/app/fluxgym/models/vae/ae.sft" \
|
| 9 |
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--cache_latents_to_disk \
|
| 10 |
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--save_model_as safetensors \
|
| 11 |
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--sdpa --persistent_data_loader_workers \
|
| 12 |
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--max_data_loader_n_workers 2 \
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| 13 |
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--seed 42 \
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| 14 |
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--gradient_checkpointing \
|
| 15 |
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--mixed_precision bf16 \
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| 16 |
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--save_precision bf16 \
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| 17 |
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--network_module networks.lora_flux \
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| 18 |
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--network_dim 4 \
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| 19 |
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--optimizer_type adamw8bit \--sample_prompts="/app/fluxgym/outputs/aurvena/sample_prompts.txt" --sample_every_n_steps="200" \
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| 20 |
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--learning_rate 8e-4 \
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| 21 |
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--cache_text_encoder_outputs \
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| 22 |
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--cache_text_encoder_outputs_to_disk \
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| 23 |
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--fp8_base \
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| 24 |
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--highvram \
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| 25 |
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--max_train_epochs 22 \
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| 26 |
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--save_every_n_epochs 4 \
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| 27 |
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--dataset_config "/app/fluxgym/outputs/aurvena/dataset.toml" \
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| 28 |
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--output_dir "/app/fluxgym/outputs/aurvena" \
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| 29 |
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--output_name aurvena \
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| 30 |
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--timestep_sampling shift \
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| 31 |
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--discrete_flow_shift 3.1582 \
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| 32 |
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--model_prediction_type raw \
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| 33 |
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--guidance_scale 1 \
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| 34 |
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--loss_type l2 \
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