Fine-tuning Llama 2 70B using PyTorch FSDP

fine-tuning a 70b parameter model is pure pain. using FSDP is necessary because you can't fit that beast onto a single GPU, but it introduces a massive layer of complexity that eats up developer time. it's not just about the math; it's about distributed memory management and communication overhead.

we're talking about coordinating hundreds of GPUs, and mismanaging the sharding can lead to silent failures or ridiculously slow training loops. the setup costs and the debugging time for FSDP are insane for a small team.

honestly? you're spending more time setting up the distributed environment than actually tuning the model weights. it requires specialized infra knowledge that most engineers don't have by default.