@Furkan Gözükara SECourses those were great pointers, but i'll come back to this problem another tim
@Furkan Gözükara SECourses those were great pointers, but i'll come back to this problem another time. thanks for the help!
Fyou are welcome
R@Furkan Gözükara SECourses I am attempting to train a Lora following your video, however I am getting this error when clicking (Train).
Traceback (most recent call last):
File "/workspace/kohya_ss/train_network.py", line 783, in <module>
train(args)
File "/workspace/kohya_ss/train_network.py", line 146, in train
text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype, accelerator)
File "/workspace/kohya_ss/library/train_util.py", line 3023, in load_target_model
text_encoder, vae, unet, load_stable_diffusion_format = _load_target_model(
File "/workspace/kohya_ss/library/train_util.py", line 2989, in _load_target_modelRHow could I solve this?
RI looked in my files and I am missing the train_network.py, file
RI read all of these solutions and tried, them but none worked, https://www.reddit.com/r/StableDiffusion/comments/114e0nj/kohya_ss_error_how_do_i_solve_this/
reddit
3 votes and 33 comments so far on Reddit
Fi dont see error messsage here. but try adamw instead of adam8bit
RI did, same result
Rsubprocess.CalledProcessError: Command '['C:\\Stable-Diffusion\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5', '--train_data_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/image/', '--resolution=512,512', '--output_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/model', '--logging_dir=C:/Stable-Diffusion/Emma/Process lora/Emma lora/log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--network_weights=C:/Users/archi/Downloads/LoraLowVRAMSettings.json', '--output_name=last', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=150', '--train_batch_size=1', '--max_train_steps=1496', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--seed=1234', '--cache_latents', '--bucket_reso_steps=64', '--mem_eff_attn', '--gradient_checkpointing', '--xformers', '--use_8bit_adam', '--bucket_no_upscale']' returned non-zero exit status 1.
Khow would i use the dev version on the colab? I'm using TheLastBen's colab here: https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
Fwell this may not work as good as on pc
Fthat is why
Fyou can use runpod alternatively
ROk, thank you
Kmy pc doesn't have enough vram, so i paid for google colab compute GPUs. i guess if i pay for runpod then it'll work?
Fyes runpod works
Fi have necessary tutorials
FGitHub
Best Stable Diffusion and AI Tutorials, Guides, News, Tips and Tricks - GitHub - FurkanGozukara/Stable-Diffusion: Best Stable Diffusion and AI Tutorials, Guides, News, Tips and Tricks
Fsearch runpod word
Fi am going to sleep hopefully see you tomorrow
Kthank you! is there a way to use google colab to do it? just because i already have some compute on google colab and don't want to waste them
Tme: i don't really understand truncation error with regards to image diffusion samplers. can you lay it out in eli5 terms for me?
ChatGPT said:
Sure! Let's say you're baking cookies and the recipe calls for 1/3 cup of sugar. But your measuring cups only have 1/4 cup and 1/2 cup.
If you use the 1/4 cup, you won't be adding enough sugar. If you use the 1/2 cup, it will be too much. So, you decide to fill the 1/4 cup and add a little bit more, hoping it's about 1/3 cup.
The difference between the amount of sugar you actually added and the exact 1/3 cup the recipe called for is like the truncation error. It's a small error that comes from having to stop (or "truncate") your measuring because you don't have the exact tool (in this case, the right measuring cup) to get the precise amount.
In the case of the image diffusion, the "sampling steps" are like the measuring cups. If you could do an infinite number of steps, you could get the exact, perfect result. But in reality, you have to stop at some point (just like you can't keep adding sugar forever), and this results in a small error. Increasing the number of steps is like adding a bit more sugar to the 1/4 cup to try and get closer to the exact 1/3 cup you need.
ChatGPT said:
Sure! Let's say you're baking cookies and the recipe calls for 1/3 cup of sugar. But your measuring cups only have 1/4 cup and 1/2 cup.
If you use the 1/4 cup, you won't be adding enough sugar. If you use the 1/2 cup, it will be too much. So, you decide to fill the 1/4 cup and add a little bit more, hoping it's about 1/3 cup.
The difference between the amount of sugar you actually added and the exact 1/3 cup the recipe called for is like the truncation error. It's a small error that comes from having to stop (or "truncate") your measuring because you don't have the exact tool (in this case, the right measuring cup) to get the precise amount.
In the case of the image diffusion, the "sampling steps" are like the measuring cups. If you could do an infinite number of steps, you could get the exact, perfect result. But in reality, you have to stop at some point (just like you can't keep adding sugar forever), and this results in a small error. Increasing the number of steps is like adding a bit more sugar to the 1/4 cup to try and get closer to the exact 1/3 cup you need.
Thow correct did chatGPT get this i wonder?
生hey guys i try this vedio but the cmd show this is means i dont process in GPU? my gpu is RX6600
生YouTubeSECourses
Databricks’ #Dolly v2 is a free, open source, commercially useable ChatGPT-style #AI model. Dolly 2.0 could spark a new wave of fully open source LLMs similar to #ChatGPT . Open source community working hardest to bring up a model that can compete with GPT4. Our discord: https://bit.ly/SECoursesDiscord
If I have been of assistance to you and yo...
If I have been of assistance to you and yo...
生
Ti'm a nooby, but from what others have told me, AMD doesn't work well with machine learning stuff like stable diffusion (yet)
生oh that too bad QQ
Ti'm not familiar with the specific error message your seeing, so maybe someone can give better help. i'm not saying AMD can't run stable diffusion
Tjust that it isn't as stable as an nvidia card or as easy
生alright i will try this again with my own computer
生thx
Tgood luck
AWas wondering if there is any way to instruct SD (A1111) within prompt to only apply lora to specific subjects? Say I have a lora that generates specific person, if I put few subjects it will usually apply lora to them to all, is there a way to limit lora's influence to only one specific subject without having to use regional prompt or other similar extensions?
Uyes there is, you need to learn to use latent couple and masking
Ualso if people werent aware https://discord.com/invite/stablediffusion
Utheyre letting you test and vote on SDXL (reportedly 50% done)
Uive 3 prompts currently in the current round of voting which is neat
UI see now you are asking without using those extensions. your best bet becomes inpainting i guess.
Ui really recommend latent couple tho since it lets you create masks and define each one in a single prompt, ill give example:
Uusing control net plus latent couple i could define all 6 characters. i can bring them out a lot more with more control nets and defined details
Uthetres a lot of room for flexibility with the modified softedge_hedsafe control net im using
Uthe bottom right image is the latent couple mask, the colors are arranged in order that they'll fill out in the form underneath, white being the general prompt for scene with left to right in color being each character. you can do it with loras. there was a bug for a bit using loras in prompts, but i think tehy fixed it? so if you were to make an openpose control net and latent couple each pose similar to how my masking was done, your prompt would read:
generral scene of scene-like things and such BREAK
AND <lora A:0.6> BREAK
AND <lora B:0.6> BREAK
AND <lora C:0.6> BREAK
AND <lora D:0.6>
generral scene of scene-like things and such BREAK
AND <lora A:0.6> BREAK
AND <lora B:0.6> BREAK
AND <lora C:0.6> BREAK
AND <lora D:0.6>
Uyou have to use those steps tho if you want to do what you're talkingabout in one generation
UI am not using loras for my image, but this is the only way i know how. i know you wanted a different answer but hope this might help
Ubetter render and more info
Ffor google colab it is not working as good as on your pc
FChatGPT has no idead about stable diffusion yet. but i am planning an in depth tutorial for this
Fhi. probably they dont support amd right away. there could be way to make it work but i havent tested
Fyou are using latent couple extension? this is something i plan to cover
