Every billion parameters needs about 2 GB of VRAM - if using bfloat16 representation. 16 bits per parameter, 8 bits per byte -> 2 bytes per parameter.

1 billion parameters ~ 2 Billion bytes ~ 2 GB.

From the name, this model has 72 Billion parameters, so ~144 GB of VRAM

CUDA 11.4 and above are recommended (this is for GPU users, flash-attention users, etc.) To run Qwen-72B-Chat in bf16/fp16, at least 144GB GPU memory is required (e.g., 2xA100-80G or 5xV100-32G). To run it in int4, at least 48GB GPU memory is requred (e.g., 1xA100-80G or 2xV100-32G).

It's derived from Qwen-72B, so same specs. Q2 clocks it in at only ~30GB.

Just a data center or two. Easy peasy dirt cheapy.

I think I read somewhere that you'll basically need 130 GB of RAM to load this model. You could probably get some used server hardware for less than $600 to run this.

Around 48gb of VRAM if you want to run it in 4bits

Unfortunately LLMs need a lot of VRAM. You could try using koboldcpp, it runs on the CPU but let's you offload layers onto the GPU. That way you might be able to stay withing those 4gb even with larger models.

Edit: I forgot to mention there's a fork of koboldcpp with rocm for AMD cards, which is about twice as fast if I remember correctly. Only relevant if you have an AMD card tho.

Edit 2: This is the model I use btw

4GB is practically nothing in this space. Ideally you want at least 10GB of dedicated vram if you can't get even more. Keep in mind you're also probably trying to share that vram with your operating system. So it's more like ~3GB before you even started.

Kolboldcpp is capable of using both your GPU and CPU together, you might wanna consider that. (Using a feature called layers) There's a trade-off that occurs between the memory available and the quality of its output and the speed of the calculation.

The model mentioned in this post can be run on the CPU with enough system ram or swap.

If you wanna keep it all on the GPU check out 4bit models. Also there's been a lot of work into trying to do this with the raspberry Pi. I suspect that their work could help you out here as well.

Depends on your needs. Best look around in !localllama@sh.itjust.works or similar. (I don't wanna say reddit but r/localLlama is much larger.)

If you're more into creative writing, maybe look for places that discuss SillyTavern (r/SillyTavernAI is an option). It's software for role-play chats, which may not be what you want. But the community is (relatively) large and likely to have good tips for non-coding/less technical applications.

Since I had an okay experience with EasyDiffusion I tried running text gen locally through oobabooga, but no matter which model I load, it just crashes whenever it tries to generate anything, regardless if it runs through the UI's chat or SillyTavern. No error in the terminal either, it just stops and throws me back into the command line.

Large Language Model AI. Like ChatGPT.