201–210 of 241 posts
A CUDA supported graphics card with >= 11gb VRAM (and CUDA installed) or an M1 processor. /Sighs in Intel iMac Has anyone managed to get an eGPU running under MacOS? I guess I could use Colab but I like the feeling of running things locally.
I'm told Imaginairy secretly does run on Intel Mac. very slowly. I just don't want to be on the hook for support so the reqs are written that way.
What are the most affordable GPUs that will run this? (it said it needs CUDA, min 11GB VRAM, so I guess my relatively puny 4GB 570RX isn't going to cut it!)
Can you imagine only being able to cook a hamburger on one brand of grill? But you can make something kinda similar in the toaster oven you can afford? I want to be productive on this comment… but the crypto/cuda nexus of GPU work is simply not rational. Why are we still here? You want to work in this field? Step 1. Buy an NVIDIA gpu. Step 2. CUDA. Step 3. Haha good luck, not available to purchase. This situation is…
1. It's just not a huge deal to many people. Most people who want to do local ML training and inference can just buy a NVIDIA GPU.
2. AMD only has a skeleton team working on their solution. It's clear it's not a focus.
What are the most affordable GPUs that will run this? (it said it needs CUDA, min 11GB VRAM, so I guess my relatively puny 4GB 570RX isn't going to cut it!)
Can you imagine only being able to cook a hamburger on one brand of grill? But you can make something kinda similar in the toaster oven you can afford? I want to be productive on this comment… but the crypto/cuda nexus of GPU work is simply not rational. Why are we still here? You want to work in this field? Step 1. Buy an NVIDIA gpu. Step 2. CUDA. Step 3. Haha good luck, not available to purchase. This situation is…
Because nvidia spent a long time chasing the market and spending resources, like they wanted it.
You wanted to learn about GPU compute in 2012? Here's a free udacity course sponsored by nvidia, complete with an online runtime backed by cloud GPUs so you can run the exercises straight from your browser.
You're building a deep learning framework? Here's a free library of accelerated primitives, and a developer who'll integrate it into your open source framework and update it as needed.
OpenCL, in contrast, behaves as if every member of the consortium is hoping some other member will bear these costs - as if they don't really want to be in the GPU compute business, except out of a begrudging need for feature parity.
And in terms of being rational - if you're skilled enough to be able to add support for a new GPU vendor into an ML library, you're probably paid enough that the price of a midrange nvidia GPU is trivial in comparison.
All is not lost, though - vendors like Intel are increasingly offering ML acceleration libraries [1] and most neural networks can be exported from one framework and imported into another.
[1] https://www.intel.com/content/www/us/en/developer/tools/onea...
Fireworks. These AI tools seem very good at replacing textures, less so about inserting objects. They can all "add fireworks" to a picture. They know what fireworks look like and diligently insert them into "sky" part of pictures. But they don't know that fireworks are large objects far away rather than small objects up close (see the Father Ted bit on that one). So they add tiny fireworks into pictures that don't ha…
Here is a colab you can try it in. It crashed for me the first time but worked the second time. https://colab.research.google.com/drive/1rOvQNs0Cmn_yU1bKWjC...
EDIT - it's free of charge: https://research.google.com/colaboratory/faq.html --- First time I've used "colab" - looks great. Out of interest, who pays for the compute used by this? Is it freely offerred by Google? Or is it charged to my Google API account when I use it? Or your account? It wasn't clear in the UI.
I've been toying with SD for a while, and I do want to make a nice and clean business out of it. It's more of a side-projecty thing so to speak. Our "cluster" is running on a ASUS ROG 2080Ti external GPU in the razer core-x housing, and that actually works just fine in my flat. We went through several iterations of how this could work at scale. The initial premise was basically the google homepage, but for images. Th…
Your queue decouples demand from supply - though you now have another problem - if demand far exceeds supply will your queue overflow?
In that scenario you might need to push the queue back to the requester - ie refuse the job and tell them to resubmit later.
I am not a fan of software such as this putting in an arbitrarily "safety" feature which can only be disabled via undocumented environment variable. At least make it a flag documented for people who don't have an issue with nudity. There isn't even an indication that there is a "safety" issue, you just get a blank image and are wondering if your GPU/model or install is corrupted. This isn't running on a website that…