I am attempting to train a LERF model on a custom dataset containing approximately 2000 images. When I run the 'ns-train' command, my 32GB of RAM becomes fully utilized, resulting in the termination of the process. Previously, I have successfully trained standard NeRF models using NeRF Studio on the same dataset without any issues. Therefore, I am wondering whether 32GB of RAM is insufficient for training LERF models, or if I might be missing a specific command necessary for LERF training. I have also tried reducing the number of images in my dataset, but this approach did not resolve the issue. The command I am using for training is:
Hi all,
I am attempting to train a LERF model on a custom dataset containing approximately 2000 images. When I run the 'ns-train' command, my 32GB of RAM becomes fully utilized, resulting in the termination of the process. Previously, I have successfully trained standard NeRF models using NeRF Studio on the same dataset without any issues. Therefore, I am wondering whether 32GB of RAM is insufficient for training LERF models, or if I might be missing a specific command necessary for LERF training. I have also tried reducing the number of images in my dataset, but this approach did not resolve the issue. The command I am using for training is:
ns-train lerf --output-dir --data data/colmap/
Thank you so much for your help.