| Windows Registry Editor Version 5.00 | |
| [HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\BackgroundAccessApplications\Microsoft.Windows.ContentDeliveryManager_cw5n1h2txyewy] | |
| "Disabled"=dword:00000001 | |
| [HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\ContentDeliveryManager] | |
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tips on setting up a custom environment for hypergan
This guide requires Anaconda. Download and install Anaconda3 from:
https://www.anaconda.com/download/
Before you start anything with HyperGAN, you must install the CUDA libraries. If you don't have a CUDA GPU, I wouldn't recommend reading this guide further since this guide assumes you will be using a CUDA powered GPU.
Get cudnn here: https://developer.nvidia.com/cudnn
This worked on 14/May/23. The instructions will probably require updating in the future.
llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)
Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.
08737ef720f0510c7ec2aa84d7f70c691073c35d.