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throw_me_uwu | 4 months ago

Because ML infra is bloatware beyond belief.

If it was engineered right, it would take:

- transfer model weights from NVMe drive/RAM to GPU via PCIe

- upload tiny precompiled code to GPU

- run it with tiny CPU host code

But what you get instead is gigabytes of PyTorch + Nvidia docker container bloatware (hi Nvidia NeMo) that takes forever to start.

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