Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
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sudo apt-get remove --purge '^nvidia-.*' | |
sudo ubuntu-drivers autoinstall | |
sudo reboot |
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import pytorch_lightning as pl | |
... | |
# override this method on pytorch-lightning model | |
def on_predict_epoch_end(self, results): | |
# gather all results onto each device | |
# find created world_size from pl.trainer | |
results = all_gather(results[0], WORLD_SIZE, self._device) | |
# concatenate on the cpu | |
results = torch.concat([x.cpu() for x in results], dim=1) | |
# output will not preserve input order. |
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# NOTE: | |
# You can find an updated, more robust and feature-rich implementation | |
# in Zeno Build | |
# - Zeno Build: https://github.com/zeno-ml/zeno-build/ | |
# - Implementation: https://github.com/zeno-ml/zeno-build/blob/main/zeno_build/models/providers/openai_utils.py | |
import openai | |
import asyncio | |
from typing import Any |