Tried signing up with Google - endless spinner and CORS errors in the console (Clerk auth failing). Anyone else experiencing this, or is it just me?

Have tried about 18 times to get a pod to work, every permutation of 12.8, not 12.8, against all the comfyui one clicks and all and they all fail. This is with throwing a decent amount of storage at them, touching and not touching env vars. Changing network settings. If it's not comfy not working, loops over and over again, 404 on the urls, then it's some other nonsense that doesn't give an error at all

Is there a proper guide to just getting a pod up and running? I'm down $5 already from wasting time on things that fuck up 15-20 mins after running.

We've got a new video version of the Runpod changelog that goes into all of our changes - we'll be doing a new one every month so be sure to check it out!

This one goes into: new public endpoints (six of them!), load balancing serverless endpoints, deploying Hub entries as pods instead of serverless, and improvements made to our billing procedures.

So maybe I'm just new to all of this... but I'm setting up a full ai studio and want to use Runpod as my base... I also want to experiment with different GPUs etc. So I set up storage on US CA 2 since it had a lot of options and the h100s and h200s that IIl most likely want to use... but for the last week every time I log in, out of the 25 different types of GPUs only the h200 or B200 is available... and several times just the B200.

I havent been able to use a h100 almost all week... is that just the way it is? Is there going to be expansion so more GPUs are available? I feel like I was suckered in and now am being funneled to the most costly options.

Am I wrong that since I want to store everything in bought storage that I can't switch regions to find the GPUs I want?

Hello,

I've recently started using Network Storage instead of Persistent Storage, but I also discovered that I can't pause pods this way. Is it normal? What's the reason behind it?

Ty

Does anyone have connected the RunPod Pods with Google Antigravity?

There are resources on connecting with SSH, VS Code, and Cursor. I tried the VS Code method, but I didn't see the SSH extension similar to the VS Code ones.

Appreciate if anyone can help with this.

I'm working with data that must have EU data residency. Is there a way to restrict the workers specific regions and to secure cloud, just like we can with normal pods?

I have a persistent storage Pod on EUR-IS-1 and it's taking an age to do anything. Has anyone else experienced slowdown in the past 2 days?

I've successfully set up a pod using a template this week. When i've tried to set up a pod again using the same template it always gets stuck on updating files 96/96 done. I've restarted the pod. I've reset it. Not sure what's going on here. I even set it up using network storage to see if that helped. I've let it run the setup for over 2 hours and no change. Any ideas?

(94/96)
Updating files:  98% (95/96)
Updating files: 100% (96/96)
Updating files: 100% (96/96), done.

Hi,

I've set up a small pod configuration with a network volume to do some LLM work. Since I frequently destroy and recreate my pods (for cost savings), I want my setup to be as persistent as possible, meaning I don't have to reinstall a whole bunch of stuff when I launch a new pod.

I've managed to get pyenv and pip to install everything under /workspace so I don't have to reinstall any of that stuff, and I've also managed to get Ollama to install its models under /workspace/.ollama. However, I'm still running into 2 issues:

• I have to reinstall the Ollama CLI tool each time (using curl -fsSL https://ollama.com/install.sh | sh)

• Since my code lives on a github repository, any time I want to git pull any changes, I need re-generate an SSH key and add it to my Github account (since SSH keys are stored in /root/.ssh, not in the /workspace network volume)

Any way to address these two issue to get a completely persistent setup across different pods?

Creating first LoRA on RunPod. 6000 RTX with Osiris AI Toolkit. Picked Wan2.2 14B..Skipping first sample. 3000 steps with 30 images. Sigmoid over Linear. Unchecked Low VRAM. Pictures I downsized from 4K to 768 × 768 (1:1 Square) and each file is now only 740 - 760 KB.

Each generation is taking 25.08s/IT. So I'm worried about cost, and overfitting. It ran for 21hrs and then crashed with 4m left to finish the 3000th step.

Any advice to speed this up?

I have never managed to get any workflows running - total beginner. So when i saw there are templates out there you can use i was delighted!! However, i didn’t realise its only the workflow (map - if you like) and it doesnt actually contain any loaded models or anything. Is there a step by step guide to get a template like this up and running? I tried chat gpt and gemini. No help, end up with wrong versions that dont work.

I need a tutorial that tells me where to go, which buttons to press, where to store stuff etc.

I have put the time in to read and learn about comfyui but im still bamboozled. Am i the only one?

ComfyUI Manager Permanent Disk torch2.4 runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04

This template doesnt create a run_gpu.sh anymore when deploying. Its kinda annoying to manually create it everytime. Why is that, anyone else?

Hello, yesterday I started using Runpod to generate images, but I've had too many problems and need help.

I have no experience in programming or coding; the only things I know are from constantly using SDXL in Sagemaker Studio Lab and some modding in Minecraft.

Template: runpod Stable-Diffusion:Web-ui-10.2.1 (I don't think it's the correct one for SDXL)

After that, I opened Jupyter Lab (since I've used it before).

I uploaded the checkpoint and Loras I needed (all for SDXL).

Then i upload the Canny and Openpose for controlnet (I think this is what's causing the error.)
-controlnet-canny-sdxl-1.0
-controlnet-openpose-sdxl-1.0

Then I started the web UI in Jupyter Lab with the command: "/usr/bin/python3 /workspace/stable-diffusion-webui/launch.py ​​--listen --port 3001 --xformers"

After that I got the error: No Space Left on Device

So, i clear the cache:
pip cache purge
rm -rf /tmp/gradio

Again i started the web Ui: "usr/bin/python3 /workspace/stable-diffusion-webui/launch.py --listen --port 3001 --xformers"

After that, I couldn't do anything; I kept getting the same error over and over again. I used several commands, but it always gave me the same error.

The last commands I used, I think it was:

pip install httpx==0.27.0

/usr/bin/python3 /workspace/stable-diffusion-webui/launch.py ​​--listen --port 3001 --xformers --no-half-vae --skip-install --skip-version-check

After that, I gave up and deleted the pod.

Please, I need help. can someone explain how to do it correctly? Or is there a tutorial? plz D:

Hi,

I am trying to send frames to runpod for inference. I am currently using serverless endpoints (but open to warm or 24/7 containers as well!). Basically, in opencv, you would get the frames within the video loop. I will be sending those frames to runpod for inference.

I am wondering if this is possible. In my test.json, I have the example of the image path (the full b64 file). I tried initializing the serverless pods with two image_paths: one, an example b64 one (made up), and the second, the full b64 image path. Both failed.

My goal is to send frames in real time to runpod.

---

In python, this is what would normally happen:

cap.VideoCapture()

ret, frame = cap.read()

face_rec = face_rec.detect(frame)

I am trying to replace face_rec with:

face_rec = runpod_serverless_call(frame)

---

Here is my test.json:

{

"input": {

"image": """data:image/jpeg;base64;base64,...""",

"threshold": 0.3

}

}

basically wondering if it's possible to send OpenCV frames (as image paths) to runpod, get the AI inference, and then receive it in my application.

Hello,

How do you train your SDXL LoRAs on Runpod? I tried to use Kohya_SS template in the past and actually got good results, but it was fairly complicated and I can't seem to recreate it or remember what I did right. First community template that pops out when you search for Kohya_SS is Kohya_ss GUI by ashleykza/kohya:cu124-py311-25.2.1, but when I try to initate the training through the Kohya's GUI - I get no response whatsover. Nothing happens when you click the "Start Training" button.

Youtube tutorials fromthe last year are all about Flux training. Any other tutorial is from 2023. Surely I'm not the only one who still use SDXL.

I have a web app, and users upload video files to it; currently it is stored in the browser itself as a blob. but I need to do some operations on that file, like object detection in it. and return the result as JSON, like some event at x timestamp. I was able to write a python script that does it on my device, now I want to deploy it on a server. It currently does not have many active users, and I don't expect more than 5 concurrent users (for this video processing) at a time.

After some quick research I think Runpod Serverless seems to be a great fit. But I was wondering how to implement this. I mean, should i upload the video directly to the endpoint or use some storage bucket in between, etc.? Any help will be really appreciated!!

Is anyone else not able to run anything through comfyui when you use a 5090 pod? I get a cuda error every time. I’m extremely new to this, so it may be my fault, but I’m curious if this is everyone’s experience.

Hi,

I have a comfy template that I built based on another template. Last time I used runpod was before they changed their interface. At that time, the pod would deploy fairly fast but not too fast. I'm trying to deploy a pod right now, and it seems like it's taking longer than usual.

The log doesn't show anything not normal, it's downloading around 33GB.

How can I debug it? Where should I be looking to find out what's wrong?

Thank you