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| """ | |
| The most atomic way to train and inference a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| -- | |
| @karpathy | |
| 1. Commented out a seemingly redundant "rmsnorm" | |
| 2. Increased the width (block_size) from 16 to 32 to support long names | |
| 3. Modified the output samples so that first 50% of output starts with "sar" |