Thoughts on LoRA Training Pt 2: Where to Train

<p>

This is a pretty quick follow up, but there were some immediate "where do I start" questions I want to answer.</p>
<p>First and foremost, if you have <strong>never</strong> trained a LoRA before, start somewhere that has presets - as in a notebook or platform that has preset trianing parameter values. I beg of you. </p>
<p>The reason I insist on that is - if you go in and adjust settings before you know if you understand how to curate a dataset and captions, then you will never known if the issue is your data or your parameters. It will be a nightmare to diagnose and very discouraging. Also, most of these platforms or default settings aren't arbitrary - they've worked for <em>someone</em> at some point, so presuably you should be able to get them to work!</p>
<p>So without further hesitation, here are a list of tools I've used and some I haven't but I've seen good results from.</p>
<p><strong>OPEN SOURCE</strong></p>
<p>I think open source can be the way to go - it is certainly how I started - and it just depends on your willingness to sacrifice time for utility in many cases.</p>
<p><a href="“https://github.com/TheLastBen/fast-stable-diffusion”" rel="nofollow">The Last Ben Runpod</a></p>
<p>The simplest and TLB is fantastic. Really, if you want to just not overthink things and get started, use his runpod. I recommend keeping your captions super short with a <strong>unique token</strong> + <strong>a couple words description</strong> format. If that, honestly, Ben has always recommended just to use the unique token. Either works.</p>
<p>The only challenge of just using the unique token is that you will need to ensure you have a balanced dataset. As in - enough images but not too many (10-30), no doubles, consistency of the concepts you want to keep and variability of the things you don't want the model to learn.</p>
<p><a href="“https://github.com/bmaltais/kohya_ss”" rel="nofollow">Koya</a></p>
<p>Kohya is also great - I just hesitate to put it in front of new people because it allows you to adjust so much. I feel like that can be a recipe for disaster. But, ultimately, a gold standard.</p>
<p><strong>PAID SERVICES</strong></p>
<p>Truth be told, I haven't met a silver bullet platform, but here are all the ones I am aware of with notes on whether I've used them.</p>
<p><strong>Scenario</strong> - I actually helped develop the training presets at Scenario, so I quite like it. I believe it is still unlimited trainings for account holders, however there isn't a way to export your models which I find really challenging. I usually just use the presets.</p>
<p><strong>CivitAI</strong> - I don't love the vibe of Civit, but I would be misleading you if I said their training doesn't work. I even trust their crazy autocaptions. Typically I do 20 epochs with 17 repeats and Clip Skip of 2.</p>
<p><strong>Pimento</strong> - I am pretty impressed with the presets they have for illustration on Pimento. I haven't dug into it too deep, but ultimately I think it has a lot of promise as a service.</p>
<p><strong>Leonardo</strong> - I haven't spent a ton of time using Leonardo for training, but I wasn't wholey disappointed when I did. I do think their finetuning team makes amazing things and would love to see their training updated more to reflect that.</p>
<p><strong>Layer</strong> - I haven't used their service much myself, but I have heard people get really strong results.</p>
<p><strong>EverArt</strong> - For people who want a really really simple setup without too many changes, I think EverArt shows a lot of promise.</p>
<p><strong>Astria</strong> - I actually trained my first time on Astria in 2022, and I think they have the consistent character/object set up really well established. I haven't revisited it yet but it is on my list.</p>
<p>So - hopefully this list helps you!</p>
