Train a GPT2 model with JAX on TPU for free

Google's JAX framework enables efficient language model training on TPUs, as shown in this guide to building a GPT-2 model. The tutorial covers implementing transformer blocks with NNX, enabling SPMD parallelism across TPU cores, and optimizing training through JIT compilation. Using free TPU resources, a 124M parameter GPT-2 model can be trained in about 7 hours on a TPU v3, or 1.5 hours with Trillium. This approach achieves performance comparable to implementations like nanoGPT, providing a basis for exploring larger language models.