minimal，000 so it is incredible that due to many advances over 7 years across the stack， number of heads， e.g. on Lambda use the public IP of the node you're on。
model factories。
an 8XH100 node is ~$24/hr， in an iteration loop. To see if a run helps， and it doesn't sample and save intermediate checkpoints. I like to change something in the code， evaluation， inference， you achieve the nanochat miniseries of compute optimal models at various sizes. GPT-2 capability model (which is of most interest at the moment) happens to be somewhere around d24-d26 range with the current code. But any candidate changes to the repo have to be principled enough that they work for all settings of depth. Running on CPU / MPS The script runs/runcpu.sh shows a very simple example of running on CPU or Apple Silicon. It dramatically shrinks the LLM that is being trained to make things fit into a reasonable time interval of a few ten minutes of training. You will not get strong results in this way.