PhysX-3.4 VS nebuly

Depends if the drivers you have already have the GPU drivers already but if you want a clean slate you can use DDU first then install fresh from www.nvidia.com on the latest driver

Then, reboot and head to www.nvidia.com to download the latest drivers for your GPU.

Try it manually from www.nvidia.com, the file is at least 900mb so if you have a couple gigabytes free it should be fine

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once it gets to the point where I enter nvidiia-smi I getMNVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running. I downloaded the driver and had to run it in root where I was told I had X runnning and had to turn it off and to visit www.nvidia.com but there is no help there. I was also told to see /var/log/nvidia-installer.log for details. Any ideas?

Display driver uninstaller, remove all Nvidia GPU drivers and clean install new ones from www.nvidia.com , that will fix it.

Just go to www.nvidia.com and just install them manually

just download it from www.nvidia.com and worry about it next time

Run the program and remove and Nvidia GPU drivers that it finds. Grab the latest drivers from www.nvidia.com and try to install once DDU has removed all of the old ones. Make sure you restart after it's done.

Hi everyone. I’m the creator of ChatLLaMA https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama, an opensource framework to train LLMs with limited resources and create There’s been amazing usage of LLMs in these days, from chatbots to retrieve about company’s product information, to cooking assistants for traditional dishes, and much more. And you? What you building or would love to build with LLMs? Let me know and I’ll share the article about your stories soon. https://qpvirevo4tz.typeform.com/to/T3PruEuE Cheers

How does it differentiate from the original ChatLLaMA? https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...

Was this made with the ChatLLaMA library? https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama

Some of the available modules include:

Speedster: Automatically apply the best set of SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. https://github.com/nebuly-ai/nebullvm/blob/main/apps/acceler...

Nos: Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas. https://github.com/nebuly-ai/nos

ChatLLaMA: Build faster and cheaper ChatGPT-like training process based on LLaMA architectures. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...

OpenAlphaTensor: Increase the computational performances of an AI model with custom-generated matrix multiplication algorithm fine-tuned for your specific hardware. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...

Forward-Forward: The Forward Forward algorithm is a method for training deep neural networks that replaces the backpropagation forward and backward passes with two forward passes. https://github.com/nebuly-ai/nebullvm/tree/main/apps/acceler...