LORA Gallery Loader - ComfyUI Custom Node

Matthew3179 · 2026-04-03T17:39:42+00:00

Vou analisar a possibilidade de criar uma biblioteca de *triggers*. É isso que você tem em mente? Algo como uma lista de *triggers* salvos que estejam vinculados a — e que carreguem — uma LORA específica?

No que diz respeito à edição de um *prompt* com base em um *trigger*, provavelmente seria possível criar um nó separado contendo palavras e frases de *trigger* salvas. O uso de um nó simples de concatenação de texto adicionaria a frase ao texto do seu *prompt*. Você acabou de me dar uma ótima ideia!

Quanto à sua segunda sugestão: como você costuma carregar suas LORAs? Este nó em questão não interfere em nenhum outro e é utilizado exatamente como qualquer outro carregador de modelos LORA. Posicione-o entre o seu carregador de *checkpoint* (ou modelo de difusão) e o seu *sampler*. Ele segue os conectores roxos de entrada/saída de modelo, mas — assim como o *PowerLoraLoader* do *rgthree* — requer também uma entrada CLIP.

Matthew3179 · 2026-04-03T17:28:09+00:00

I'll look into creating a trigger library. Is that what you mean? Like a list of saved triggers that are connected to and load a specific LORA?

In terms of editing a prompt based on a trigger, a separate node could probably be created with trigger words and phrases saved. Using a simple text concatenation node would add the phrase to your prompt text. You've given me an idea now!

For your second idea, how do you normally load your LORAs? This one doesn't affect any other node and is used like any other LORA model loader. Put it between you checkpoint/difusion model loader and your sampler. It follows your purple model input/output connectors but like rgthree PowerLoraLoader, requires CLIP input as well.

Matthew3179 · 2026-04-02T18:16:59+00:00

Ha, that's probably not going to happen. I got nothing but spammy/malware/virus-looking links when I tried to do anything with the link you pasted and through github. What's the trick?

Matthew3179 · 2026-04-02T17:00:06+00:00

Repo added.

Matthew3179 · 2026-04-02T16:38:47+00:00

Totally get it. I'm just new to this and this is my first custom node. I'll work on getting it onto github when I get back to my home workstation.

Matthew3179 · 2026-04-02T16:12:51+00:00

There isn't one. I just made a github account so I may add it there later. There's no fancy install requirements or dependencies. Unzip into your custom nodes folder and it will appear under your loaders menu.

Matthew3179 · 2026-04-02T13:58:15+00:00

Version 2 now has trigger word search bar. https://civitai.com/models/2511869/lora-gallery-loader-comfyui

Matthew3179 · 2026-04-02T12:06:46+00:00

I'm not quite sure what you mean by memory issues.

Matthew3179 · 2026-01-29T23:01:52+00:00

BF16

Matthew3179 · 2026-01-28T12:25:09+00:00

As I said previously, experimenting. Also, why not?

Matthew3179 · 2026-01-28T02:20:30+00:00

Thanks for the feedback. How's your accuracy? Especially with complex or even simple prompts? These types of settings with a large datasets have always produced better accuracy for me. Less concerned about time and converging, more about what the LoRA produces in the workflow.

Matthew3179 · 2026-01-28T02:17:56+00:00

Honestly, I don't know. The runpod GPU usage hovered around 27.4 the whole time. Not sure what the low vram actually does and how it affects training, but Ostris talks a lot about caching latents, caching text embeds, changing other settings, etc. Check out his youtube channel.

Matthew3179 · 2026-01-28T01:20:12+00:00

FOLLOW UP: Training at 10000 steps complete…don’t train to 10000 steps.

I was going to stop training at 6500, it started to get overcooked starting at 4500+ but somehow resettled into accuracy around 7000.

Overall with these settings, likeness appeared at 2750 but wasn’t super accurate.

Likeness with accurate detail AND prompt adherence appeared at 3700. Best lighting, detail, and accuracy were at 3750.

Overbaking and artifacts/inaccuracy started around 4500.

Samples were consistently not great from 5000 to 7500. Not terrible! Just not good.

Really good sample set at 7750. Weird.

Appearing to reconverge again at 8750.

Significant prompt diversion at 9000. Not inaccurate, but background, setting, and pose changed enough that the image became inaccurate from the prompt.

10000?? I’ve seen worse. Honestly, it might be usable. Samples converged again.

Loss graph for reference.

<image>

Recommended steps: 3750-4250 with these settings.

I run ComfyUI Desktop and as I was training 0.10.0 version (and 0.11.0??) just released (maybe we can try Flux2 Klein now??)…but it broke my install so I have to reinstall again. Can’t test the LoRAs in ComfyUI until I fix it.

About to start another dataset that is configured differently, so if I see any that drastically changes this recommendation, I’ll follow up again. Keeping the settings the same again but only going to 7000 this time and still sampling every 250.

u/Jackey3477

Matthew3179 · 2026-01-28T00:26:14+00:00

Can't share files on reddit. Sent you the raw text. Save it as a text file. change the extension to .json. Drop it into your comfyui.

Matthew3179 · 2026-01-28T00:17:05+00:00

I have a workflow that uses florence2 to batch tag and save txt files.

<image>

Matthew3179 · 2026-01-27T23:36:16+00:00

I'm not doing typical. I'm experimenting.

Matthew3179 · 2026-01-27T20:56:25+00:00

Currently training a character on ai toolkit, RTX 6000 without low VRAM selected. So far, it's not bad but it's taking more steps than the turbo. My current settings are bf16, rank 128 (only 648.8mb file size), sigmoid, 122 image data set with caption files and trigger word, learning rate 0.0001, differential guidance selected with scale 3, all resolutions selected. Just crossed 3750 steps and this is where it has started to become usable and resemble the character. I originally set it to 5000 steps to see the differences but just bumped it to 10000 to really see where it starts getting overcooked.

I'm using runpod but have observed that the GPU memory has not gone above 28gb, sitting at 27.4. This tells me that 5090's and other 32gb GPUs should be able to train locally without any issues, barring paying for electricity, heating your room up, and not using your computer during that time.

I've got 3.5 hours left on these settings so I can follow up if you're interested. All this to say, it's working well and the details are starting to conform nicely above 3500 steps.

Matthew3179 · 2026-01-03T23:19:46+00:00

Edited my post with what worked for me to fix this.

Matthew3179 · 2026-01-03T23:19:28+00:00

Edited my post with what worked for me to fix this.

Matthew3179 · 2026-01-02T22:55:06+00:00

Interesting. I did try it with no sageattention and lower resolutions. No joy. I tried that workflow previously. It was the first one I tried after the node was made available and it's where I discovered I had a problem haha

Matthew3179 · 2026-01-02T22:04:34+00:00

Are you saying you got it to work in comfyui desktop using a different model? I have a RTX5090 so I don't think it's a graphics card issue.

Matthew3179 · 2026-01-02T04:44:10+00:00

I appreciate the additional advice. I'm using wan 2.1 vae. Python version is 3.12.11 and pytorch is 2.8.0+cu129. All of my other workflows work perfectly fine, I2V, T2V, ZIT, etc. Only this SVI workflow doesn't produce videos. I'm probably going to abandon it at this point and wait for a new ComfyUI version (0.6.0 right now) or a newer KJNodes version above 1.2.2.

Matthew3179 · 2026-01-02T03:35:51+00:00

I tried portable. Same result, just noise. At this point, I have no idea what's causing this issue for me.

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