Kohya trainer reddit Can I have settings for Kohya Prodigy with 1. when you have training images of different sizes/dimensions, it will process them together instead of separately. Recommendations. txt" in a text editor. 0 strength and I couldn’t believe my eyes how much improved the merged lora was. However, if you are training with captions or tags much different than what SDXL knows, you may need to train it. One trainer came along real late - way after Kohya had thousands of users - I think that's the reason those who enjoy the OT GUI may go a little overboard trying to recruit more love for it. Set network rank and alpha to 128, once you have a working lora you can play with lowering them to get smaller sizes. Watched many tutorials on YouTube, after watching I notice there are many mixed and opposite practises and guides. LoRA are relatively small, and the vram gained Huge news for Kohya GUI - Now you can fully Fine Tune / DreamBooth FLUX Dev with as low as 6 GB GPUs without any quality loss compared to 48 GB GPUs - Fine Tuning As my card has fewer vram (8GB) than what is recommanded (12GB minimum), I have changed quite a bit the original guide of am7coffeelove to adapt my configuration and the Training with a resolution of 512 seems to produce excellent results – much better and faster than 1024x! Apparently flux lora is very different from SDXL lora training. 0001. Any help would For a long time, I had no idea what the various options on Kohya did and searching Google didn't get me much either for many of them. I am able to train 4000+ steps in about 6 hours. Hi my laptop specs are: i7-8750H - 6 cores (x2 threads). I trained with 50 images (with 50 captions), 10 repeats, 10 epoch, with default learning rate of 0. I don't know anything about . So far I used the trainer with SDXL basemodel, but i'd like to train new Loras using Ponydiffusion. Training with a constant factor is like driving with a constant speed:. For instance, if you have a training image that is 1664x2432 (13:19 ratio), Kohya will first downsize this to 832x1216, the put it in the 13x19 bucket. Although that may be true and it can be ignored, it does cutdown on training time. Also keep in mind that aspect ratio matters a lot so generate using the training AR or else make sure you get a variety of AR in the training set (even including duplicates with various cropping). However, I’m still interested in finding better settings to improve my training speed and likeness. I'm kinda new to training but I was able to follow guides from this sub and trained with kohya_ss UI with Lora and got decent results. " For large finetunes, it is most common to NOT train the text encoder. it took 13 hours to complete 6000 steps! One step took around 7 seconds to complete I tried every possible settings, optimizers. A few months ago, Nvidia released a driver update allowing applications Your still best off (imho) using kohya's script to do SDXL dreambooth training. Then I tried cutting down my dataset size, training steps per image, and only used 1 epoch. Trying to balance some new parameters out with kohya_ss, results are so so. true. But also, the faster you drive the more likely it is that you'll miss your parking lot. 16 GB RAM. I find it helpful to include regularization images at a 1:4 ratio to training images*. Also, if you give Kohya a training image that is bigger that the sizes listed below (more pixels, same ratio) it will first downsize the image. My understanding is that Kohya takes this folder name and uses the first part for the number of repeats and the second part for my instance prompt. Does anyone know of a When doing Kohya DreamBooth training, our ground truth manually collected 5200 man regularization images dataset used with caption of “man”. This is a great tutorial (posted it below also, but yea it'll get you going): Trying to balance some new parameters out with kohya_ss, results are so so. Preparation of this Tick or untick the box for "train text encoder. Settings that use more VRAM than you have can cause the trainer to start using RAM, which is significantly slower. Got the Kohya GUI working Selected 20+ sample training images of a subject (person from various angle and clothing) (for now I didn't put any regulation images) Selected LoRA tab and used GUI to set up the folders (img, log, model) I’ve been using SD for 4 months and SDXL since beta. so it's win/win this is actually recommended, cause its hard to find /rare that your training data is good, i generate headshots,medium shots and train again with these, so i dont have any training images with hands close to head etc which happens often with human made art, this improves training a lot, or you can try to fix and inpaint first training set but its harder if you dont have that style I want to train a lora on about 1000 images consisting of about 20 unrelated concepts. Hi, I use Linaqruf's Colab Kohya trainer XL for SDXL ( /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. I would like to discuss if Current LoRA (Kohya) training guide? I'm just starting out training LoRA on a 3090, never having done it before, and am getting lost in a plethora of out of date guides. I've been messing with Lora training using this Kohya web GUI, and so far everything works. Instead, I recommend studying this video. If you resumed training and stopped it once it reaches the original number of training steps minus the steps completed during the first training, you'll have a model that was trained the same amount of steps as one run. Over the past many years, I've subscribed to various pretty girl style subreddits, and when I see a pretty girl, I look for her on Instagram and if I like her stuff I subscribe. so about 1500 steps, which is usually a good number. The faster you drive the quicker you'll get there. 5 it will get it for you, I've been playing with Kohya_ss gui Lora trainer and it seems like it takes around 2-7 hours to train one model. with Stable Diffusion (Auto1111 and Kohya) two months ago and have a lot to learn still. I used kohya ss to merge them at 1. It is possibly a venv issue - remove the venv folder and allow Kohya to rebuild it. Think of the training rate like the speed you are driving your car. Although it does lose the (overfit) exact style of specific training images a bit, that is for the most part a good thing, as it makes way more detailed and diverse results. After a bit of tweaking, I finally got Kohya SS running for lora training on 11 images. Add the following line before "-r requirements. I'm using AdamW or AdamW8bit and getting black images all the time. When I use Network Rank 8 with Network Alpha as 1, my LoRA works fine but when I change these two 11 votes, 28 comments. everything else looks fine too, except you should keep buckets enabled. 02it/s with basic parameters: Am I doing it wrong? Is it too slow? could not find any benchmarks. I watched this video where he takes just 6 minutes! I'm obviously using an older card (I'm on a 1080ti with 12gb vram) but surely it shouldn't be THAT much slower? Training faces, I leave most everything at the default. I set LR scheduler to cosine with restarts, LR warmup to zero. I don't think the quality/performance is really This 'feature' can mask scenarios where the trainer consumes more VRAM than your GPU has, significantly slowing down the training process. Of course there are settings that are depended on the the model you are training on, Like the resolution (1024,1024 on SDXL) I suggest to set a very long training time and test the lora meanwhile you are still training, when it starts to become overtrain stop the training and test the different versions to pick the best one for your needs. if you don't have training images of different sizes/dimensions, it simply won't change anything. I'm using kohya-LoRA-trainer-XL for colab in order to train SD Lora. I'm playing around with Kohya just to test out things and what it would mean to train a LoRA. In your case, it doesn't say it's out of memory. 0 and 1. As for the other issues you're facing with training in Kohya, I don't know what the problem might be. If it's being used, adjust your training settings to ensure only GPU memory is utilized. In Kohya, the training images folder has the structure "5_myconcept". During this time, I’ve trained dozens of character LORAs with kohya and achieved decent results. It is what helped me train my first SDXL LoRA with Kohya. I tried unet only, no buckets, 768 resolution, and experimenting with different optimizers. After I clicked start trainning, I was expecting to hear a noticeable increase in fan noise from my graphics card, but that didn't Bf16 is low-precision, high-range, and is intended for mixed precision training rather than being the precision of the entire model. ipynb files but I'm guessing it's some sort of preset for Kohya? If it is, don't use it. txt" and save. So I collected about 50 images of manly parts from various sources to start the training. Idk about the 4090, but he does have some new ones up about training SDXL LoRA models with Kohya You can train SDXL LoRAs with 12 GB. To train my own model, and if it’s any good publish it. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will yeah, do 22 images, 40 steps, 2 epochs, when you set your steps, it creates a folder inside Lora folder on left side where file explorer is, dig into it, youll find a folder named 40_nameofyourthingy , you have to put images in there, pick model 1. It's got the art style (water color) pretty good. Still can't get the training below 30 hours. . However, I noticed that in the Parameters tab, there's an option to generate sample preview images of the model in the middle of training, allowing you to set it so that after ever x amount of steps, it generates a sample preview image of the Lora, allowing you to visually track the Seen a couple of posts about triton and most people mention it's not needed for training with Kohya. While searching through the GitHub Repo for what "VAE batch size" was, I finally found the trove that is the LoRA Options Documentation page: After that, it's a case of having good training images. This is better than using several training folders with various repeats # and better than training with the high quality images only. I understand how to calculate training steps based on images, repeats, regularization images, and batches, After a multiple tries, I wasn't able to get training down to a reasonable speed. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. Batch size 1. I think the training seed is only to get the training samples keeping the same seed, but correct me if I'm wrong. What kind of speed can I expect with RTX 4090 for SDXL Lora training using Kohya on Windows? I am getting around 1. Anyone having trouble with really slow training Lora Sdxl in kohya on 4090? When i say slow i mean it. etc Vram usage immediately goes up to 24gb and it stays like that during whole training. ss_session_id: "2321401183", ss_shuffle_caption: "False", A couple of days ago I tried using kohya_ss on my 3070 locally, and it pretty much froze up my system to the point where I had to hard reset. One tip is that you can upweight the training images you like most (or which are highest quality) by using multiple folders with a different number of steps. Not new, but I would like to get way much better results way more often. In the Kohya_ss folder open "requirements_windows_torch2. 5 LoRAs?. The possible caveat to that is any settings which changes over time, LR warmup, Stop text encoder training, etc. Monitor VRAM Usage: At the start of a training session, check the task manager for shared memory usage. I read many papers on how to do actual finetuning, but i was wondering how do you guys do it? Dataset preparation, number of images, captions, parameters? Have you checked out SECourses latest tutorials on YouTube? He's staying super up to date with all of the new releases and his videos have helped me train many models. Not new, but I would like to get way much better results way more often But to my surprise, kohya's training speed is surprisingly slow. Posted by u/__png___ - 5 votes and 15 comments /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. After training 100s model with dreambooth or Loras, i am now ready to try actual Finetuning with kohya or everydream trainer2. 1070 8GB dedicated + 8GB shared. hdxon kuyyen tlkjv ewbiey wtqwae cam dyrzuuc bympfs pwww iqwm