ah ok. my thought would be since once instance runs like 1-2 hours , that i could let it do 4-5 trai
ah ok. my thought would be since once instance runs like 1-2 hours , that i could let it do 4-5 trainings over night
Dbecause when i sleep i and one is done, i cant start the next one with a different checkpoint
Fi dont know if queue
Fyou can try
Jkoyha or musubi may perhaps let you train from the command line (batch)
J@Dr. Furkan Gözükara Perhaps interesting for you, trying out now for Wan22
https://civitai.com/articles/17740
https://civitai.com/articles/17740
The basis for this workflow is my original WAN2.1 training guide: My WAN2.1 LoRa training workflow TLDR | Civitai In this new article I will explai...
JSeems like it is using a seperate branch of musubi for wan22 training
Fye musubi will be also my choice
Fi will make my own gradio interface easier one
JAweomse. By the way, pro tip, I got a "flash_attn2" error running it on my RTX 5090 , however when I use the command line like this, loading CL before the loading the venv, it works just fine:
C:
cd "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build"
vcvarsall.bat x86_amd64
cl
C:\musubi-tuner
cd venv
cd scripts
activate
cd ..
cd ..
Ahi jonko
JI am sure the batch commands can be done less sloppy but the point is that CL needs to be loaded apparently
Acan you pls share results and your opinion when you finish wan 2.2 training? thanks
SHey does anyone tried a full finetune with Flux Krea ? Any samples to share/insights ? Curious
�What is the best finetune checkpoint for consistent character to avoid plastic flux look? Is krea or wan or qwan better than flux dev? I was optimistic about krea, was it not as good after all?
EAnyone know How to copy and paste in massed compute?
Cuse mouse copy and paste, not CTRL+C etc... sometimes not work at forst times.
CTraining wan2.2 High-Noise in musubi-tuner in progress.
Next Low-Noise and i will see result of my first wan2.2 lora.
Next Low-Noise and i will see result of my first wan2.2 lora.
Ethank you
Jt2v or i2v?
Jt2v works for me
C@Ella t2v. But I used just 30 photos.
- --task: t2v-A14B
- --dataset_config: dataset/dataset.toml
- --mixed_precision: fp16
- --fp8_base
- --xformers
- --optimizer_type: adamw8bit
- --gradient_checkpointing
- --learning_rate: 3e-4
- --max_train_epochs: 100
- --gradient_accumulation_steps: 1
- --seed: 5
- --optimizer_args: weight_decay=0.1
- --network_module: networks.lora_wan
- --network_dim: 16
- --network_alpha: 16
- --lr_scheduler: polynomial
- --lr_scheduler_power: 8
- --lr_scheduler_min_lr_ratio: "5e-5"
- --output_dir: output
- --save_every_n_epochs: 10
- --timestep_sampling: shift
- --discrete_flow_shift: 1.0
For High-Noise Training: - --min_timestep: 875
- --max_timestep: 1000
For Low-Noise Training: - --min_timestep: 0
- --max_timestep: 875
CToday will try in diffusion pipe.
Jprobably the epochs and learning rate can be tweaked for faster results, ill try it out
Jcan you post some results after training?
�I trained lora on a real person and still get plastic skin and plastic face in comfyui....what am I doing wrong here
Fit works with our configs
Fpeople tested but i didnt have chance yet on vacation
SWell deserved ! Enjoy your holidays 
J@Furkan Gözükara SECourses
For Musubi Tuner Wan 2.2 training, you can add the following arguments to the accelerate command, to make it generate samples
For Musubi Tuner Wan 2.2 training, you can add the following arguments to the accelerate command, to make it generate samples
--sample_prompts prompt.txt --sample_every_n_epochs 1 --sample_at_firstIn the promp.txt file you can add the positive prompt, and also some arguments (within that textfile!)
A blonde girl dancing --w 640 --h 480 --f 1 --d 1 --s 20 --n blurry
JAnyone else trainign Wan 2.2. and somehow realizing the plugging the Lora for the low model into the high model and the Lora for the high model into the low model, giving you better results?
JI checked the MD5 hash with the Hugging Face page, it's strange..
JYes, but managed to get my Cartoon style Lora finished today
J(Wan2.2 T2V Lora) - Cartoon Style Create Cartoon Style images and videos. (see examples) Use "r3tr0c0m1c" and "cartoon" as a prompt keyword. Resolu...
J
J
J
Fnice
JThanks!
Wan 2.2 is very cool, my favorite model to play with.
I just wish they would launch a controlnet version for 2.2 already.
Wan 2.2 is very cool, my favorite model to play with.
I just wish they would launch a controlnet version for 2.2 already.
JMy results so far is 3000 steps for 25 images at 2e4 learning rate, on dim 32 alpha 24, trained on 720x720 resolution.
Just a bit less than 2 hours training per model on my RTX 5090 without any offloading.
Lora strength of 1 works for 960x720 and 720x480. Needs a higher strength for higher res or if prompt gets too long.
Just a bit less than 2 hours training per model on my RTX 5090 without any offloading.
Lora strength of 1 works for 960x720 and 720x480. Needs a higher strength for higher res or if prompt gets too long.
Fnice info thanks
NI was interested in creating a Chorma lora using Kohya SD scripts. I'm thinking the issues I'm having are just my ignorance of command line. Does anyone know of a youtube or idiots guid for Kohya SD-SCripts? It's probably too much to ask for Chroma training, but if there was a Flux I think I can learn on that and eventually wing it. Thanks.
Jwhat does your command look like?
Fthis is literally gui for kohya sd scripts
FYouTubeSECourses
If you want to train FLUX with maximum possible quality, this is the tutorial looking for. In this comprehensive tutorial, you will learn how to install Kohya GUI and use it to fully Fine-Tune / DreamBooth FLUX model. After that how to use SwarmUI to compare generated checkpoints / models and find the very best one to generate most amazing image...
Aim getting very bad results
Aon wan 2.2 preset not working
NThank you in advanced. I'm almost ashamed to post it for fear I forgot something simple. I put the read me into chatgpt to try and help me create the command line and the dataset.toml file: accelerate launch --mixed_precision bf16 --num_cpu_threads_per_process 1 flux_train_network.py ^
--pretrained_model_name_or_path "D:/APPS/KohyaSD/TestModels/Chroma.safetensors" ^
--clip_l "D:/APPS/KohyaSD/TestsModels/clip_l.safetensors" ^
--t5xxl "D:/APPS/KohyaSD/TestModels/model-00001-of-00002.safetensors" ^
--ae "D:/APPS/KohyaSD/TestModels/diffusion_pytorch_model.safetensors" ^
--model_type chroma ^
--apply_t5_attn_mask ^
--cache_latents_to_disk ^
--save_model_as safetensors ^
--sdpa ^
--persistent_data_loader_workers ^
--max_data_loader_n_workers 2 ^
--seed 42 ^
--gradient_checkpointing ^
--mixed_precision bf16 ^
--save_precision bf16 ^
--network_module networks.lora_flux ^
--network_dim 4 ^
--network_train_unet_only ^
--optimizer_type adamw8bit ^
--learning_rate 1e-4 ^
--cache_text_encoder_outputs ^
--cache_text_encoder_outputs_to_disk ^
--highvram ^
--max_train_epochs 4 ^
--save_every_n_epochs 1 ^
--dataset_config "D:/APPS/KohyaSD/TestCFG/C4TS_dataset_multi_bs.toml" ^
--output_dir "D:/APPS/KohyaSD/TestOutput" ^
--output_name chroma-lora-name ^
--timestep_sampling shift ^
--discrete_flow_shift 3.1582 ^
--model_prediction_type raw ^
--guidance_scale 1.0
--pretrained_model_name_or_path "D:/APPS/KohyaSD/TestModels/Chroma.safetensors" ^
--clip_l "D:/APPS/KohyaSD/TestsModels/clip_l.safetensors" ^
--t5xxl "D:/APPS/KohyaSD/TestModels/model-00001-of-00002.safetensors" ^
--ae "D:/APPS/KohyaSD/TestModels/diffusion_pytorch_model.safetensors" ^
--model_type chroma ^
--apply_t5_attn_mask ^
--cache_latents_to_disk ^
--save_model_as safetensors ^
--sdpa ^
--persistent_data_loader_workers ^
--max_data_loader_n_workers 2 ^
--seed 42 ^
--gradient_checkpointing ^
--mixed_precision bf16 ^
--save_precision bf16 ^
--network_module networks.lora_flux ^
--network_dim 4 ^
--network_train_unet_only ^
--optimizer_type adamw8bit ^
--learning_rate 1e-4 ^
--cache_text_encoder_outputs ^
--cache_text_encoder_outputs_to_disk ^
--highvram ^
--max_train_epochs 4 ^
--save_every_n_epochs 1 ^
--dataset_config "D:/APPS/KohyaSD/TestCFG/C4TS_dataset_multi_bs.toml" ^
--output_dir "D:/APPS/KohyaSD/TestOutput" ^
--output_name chroma-lora-name ^
--timestep_sampling shift ^
--discrete_flow_shift 3.1582 ^
--model_prediction_type raw ^
--guidance_scale 1.0
JWhats the error you get?
JI think the --t5xxl needs to be a single safetensor file or pth file, and not a partial file (00001 of 00002)
