Avoid Errors by Selecting the Proper Resources for Your Pod

Runpod instances are billed based on the resources allocated, with more powerful GPUs like the A100 costing more due to their advanced infrastructure needs. When using these instances, two common errors can arise: insufficient container space and insufficient RAM/VRAM. The default 5GB container space may be inadequate when installing additional packages, causing an "OSError: [Errno 28] No space left on device" error, which can be resolved by increasing the pod's volume size, although this requires a pod reset. Insufficient RAM/VRAM can lead to "RuntimeError: CUDA error: out of memory," typically seen in computational tasks with lower-end GPUs, necessitating the creation of a new pod with a different GPU configuration. It's advisable to opt for GPUs with more VRAM to avoid such errors, as the cost difference is often negligible, and users are encouraged to seek further assistance via Discord if needed.