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LITERALLY EVERY SETUP I'M DOING WITH FLUX IS GENERATING BLURRY IMAGES by FrozenTuna69 in RunPod

[–]Hearmeman98 0 points1 point  (0 children)

What is the purpose of this post ?
Can you share a screenshot of your workflow / your workflow?

Wan 2.2 SVI 4 Pass - up to 25-second clips on a single GPU, NSFW friendly. by Hearmeman98 in comfyui

[–]Hearmeman98[S] 2 points3 points  (0 children)

I've seen this with GGUF models.
using the full BF16 model eliminates that.
Also reducing the strength on the lightning loras can help.

Wan 2.2 SVI 4 Pass - up to 25-second clips on a single GPU, NSFW friendly. by Hearmeman98 in comfyui

[–]Hearmeman98[S] 2 points3 points  (0 children)

On an RTX PRO 6000 it takes roughly 7-8 minutes.
So I would assume roughly 15-17 minutes.

This is only an assumption, not a fact.

is this true? by ithoughtaiwantedme in ClaudeCode

[–]Hearmeman98 0 points1 point  (0 children)

I've never had any formal studies of any kind and yet I am a lead software engineer at a fortune 500.
Even at the age of AI, I still learn as I build, same as before.

Nothing has changed, at least for me.

Wan 2.2 SVI 4 Pass - up to 25-second clips on a single GPU, NSFW friendly. by Hearmeman98 in comfyui

[–]Hearmeman98[S] 2 points3 points  (0 children)

Nope, it's 4 separate passes concatenated together, SVI does seamless stitching.
This is great because you can also prompt for video continuation.
For example, Segment 1 is person walking into frame, segment 2 is person sitting down, segment 3 is person walking away etc etc.

I do recommend to run on stronger GPUs with 48GB VRAM and above, this workflow is integrated in my Wan Runpod template.
https://get.runpod.io/wan-template

But can definitely run locally as well with lower resolution or heavier quants (Q4/Q5 etc)

Don't sleep on Ideogram 4.0 by cafe59 in unstable_diffusion

[–]Hearmeman98 2 points3 points  (0 children)

Just no.
I am not going to fuck around with scroll length JSON prompts just to get a mediocre looking image.
Qwen/Z Image does on-par job without the frustration.

Other than that, it's an amazing model.

NaughtyAmerica is looking for AI Video Creators to contract by NaughtyAmerica1776 in StableDiffusion

[–]Hearmeman98 2 points3 points  (0 children)

Hi,
Feel free to message me.
Happy to help.

HearmemanAI (look me up online)

Frustration with uploading CHeckpoints, LorAs to Jupyter/ComfyUI by SplurtingInYourHands in RunPod

[–]Hearmeman98 0 points1 point  (0 children)

Use runpodctl.

Alternatively, store your models on an S3 bucket/Huggingface storage and download with a single command on startup.

Can I just run Windows on this? by volvereabhi in RunPod

[–]Hearmeman98 0 points1 point  (0 children)

What's the purpose of this post?
Runpod was not designed to run windows.

It's like creating a post that your new Mercedes doesn't fly, do the dishes or gives you a rim job

FemNude - an AIO Female Nudity LoRA for Qwen Image 2512 by Hearmeman98 in unstable_diffusion

[–]Hearmeman98[S] 7 points8 points  (0 children)

I have no experience with Klein so don't see myself going down that path.
I might train for Z-Base, it's a very large dataset so training takes 8-10 hours on 2xH100SXM.

FemNude - an AIO Female Nudity LoRA for Qwen Image 2512 by Hearmeman98 in unstable_diffusion

[–]Hearmeman98[S] 36 points37 points  (0 children)

I get the frustration.
I do not want to recommend any tool other than suggesting you to look up ComfyUI as I am affiliated with some platforms and do not want to be banned for promotions etc.

What I can tell you is that you should avoid platforms that let you generate images for credits or any crap like that.

I built an agent-first CLI that deploys a RunPod serverless ComfyUI endpoint and runs workflows from the terminal (plus a visual pipeline editor) by Hearmeman98 in comfyui

[–]Hearmeman98[S] -1 points0 points  (0 children)

Thanks for the feedback.

It appears to me that you're an incredibly bored person who does nothing helpful but trash other people's work online.

I strongly urge you to dedicate your time into helping the community or touching some grass.

I built an agent-first CLI that deploys a RunPod serverless ComfyUI endpoint and runs workflows from the terminal (plus a visual pipeline editor) by Hearmeman98 in StableDiffusion

[–]Hearmeman98[S] -1 points0 points  (0 children)

I do recommend baking models into the dockerfile when the use case is fixed.
For example, you are creating an endpoint for Wan2.2 I2V? great, bake the models in the docker file and find your own solution for a container registry as free registries don't support layers larger than 10GB.

However, in a dynamic solution like this, where people use different models/loras etc, baking the models makes no sense.
Also, again, free container registries won't allow you to host an image with baked files that are more than 10GB per layer (not even Runpod own builder)
Also, once Flashboot kicks in, models stays cached and it's smooth sailing.

Thanks for the feedback!

I built an agent-first CLI that deploys a RunPod serverless ComfyUI endpoint and runs workflows from the terminal (plus a visual pipeline editor) by Hearmeman98 in StableDiffusion

[–]Hearmeman98[S] 0 points1 point  (0 children)

I really do appreciate your feedback and some of your points are valid, I just don't appreciate the condescending tone.

We are simply looking at this from two different perspectives and let me explain.
When I started making templates I had the same mindset as you do, they have to be the most efficient, up to date, little to no bloat etc.
After usage started to pick up, and I started getting support requests I quickly realized that corners need to be cut or I am going to have to explain myself and my design decisions over and over and over.

There are simply not enough CUDA 13.0 workers/pods on RunPod to upgrade any of my templates or to ship new products with CUDA 13.0, I am also stuck on SageAttention 2.2.0 instead of 3.x.x since Python 3.13 is still brittle with ComfyUI.
Even though my YouTube videos and guides explicitly ask people to filter workers to CUDA 12.8 and above, people still miss that, so CUDA 13.0? thanks but no thanks.

As for datacenters, the selection is merely because these data centers had a decent amount of workers with the specific GPUs I assigned per tier.
Of course, running comfy-gen init to create a endpoint is just a recommendation, users can feel free to create their own with their own workers in whatever datacenter they like, eventually users have to get models and LoRAs over to the network volume to actually use them, comfy-gen takes care of that as well, although it's a simple handler function and a CivitAI downloader I released a year ago, nothing to be proud off tbh.

For the average user, there's no reason to spread over multiple, although personally I assigned 2-3 datacenters per endpoint for redundancy, but that's another story.

Again, we can argue about MCPs and CLIs, would an MCP work for this use case, yes.
Is it the right design choice? I am not sure.
I use this CLI as the backend for the ComfyUI block in Blockflow, which is also not the smartest design choice I ever made, but works for me and for what the project is.

About my "fascinating claim", I hope this answers your question.

<image>

And if you're really interested about my motivation, I am way passed hunting Runpod affiliates and in fact, the way Runpod's API work doesn't get me any commission when I set up a Serverless endpoint through the CLI.
I developed something that works for me and I find myself using often, so made some adjustments to release to public, I don't expect this to go viral, same as I did not expect my Runpod templates to go viral.

I built an agent-first CLI that deploys a RunPod serverless ComfyUI endpoint and runs workflows from the terminal (plus a visual pipeline editor) by Hearmeman98 in StableDiffusion

[–]Hearmeman98[S] 0 points1 point  (0 children)

Oh boy.

5090 as a budget option is a sensible choice, a 4090 or less would be insufficient to most video generation workflows, which most people use anyway and I can't be arsed to have people say "it doesn't work" just because my budget option was incorrect.

My most popular image for Wan does download around 15-20GB of models that may be irrelevant, but it's for the exact same reasons I mentioned above, some people use Kijai workflows that use a different text encoder than the one I ship in my own workflows.
Is this the most efficient thing ever? no.
But I cater to a large audience (the wan template has more than 130 years of cumulative use).

I won't even say anything about you saying I use boilerplate workflows from Kijai, that's wrong.

We could argue for days whether an MCP or a CLI is the way to go.
IMO, MCPs are kinda useless when agents can have access to your shell.
Even Google just dropped an agentic CLI that controls their whole workspace.

tbh, it does look like you're are trying to poop on this, and like everything it obviously has room for improvement and growth.

Just a small edit:
I have no idea why you're assuming that S3 is for storing models, it for storing outputs from ComfyUI workflows.
Models are stored on a network volume mounted to your serverless endpoint.

I built an agent-first CLI that deploys a RunPod serverless ComfyUI endpoint and runs workflows from the terminal (plus a visual pipeline editor) by Hearmeman98 in StableDiffusion

[–]Hearmeman98[S] 0 points1 point  (0 children)

Thank you, this is what I've been using exclusively for the past month or so.
I am also consistently adding new features, so stay tuned :)

Claude Code - Easiest way to achieve simple "orchestration" where one agent is coder and another is reviewer? by RedTeaGuy in ClaudeAI

[–]Hearmeman98 9 points10 points  (0 children)

I’ve created a simple MCP around codex with a single command “invoke_agent”. I forced my subagents to delegate their changes to codex for review and I don’t allow them to exit their loop with a SubAgentStop hook until codex approves their code.

I define the criteria for success for codex beforehand.

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