pytorch 1.12 and above, 2.0 and above are recommended transformers 4.32 and above CUDA 11.4 and above are recommended (this is for GPU users, flash-attention users, etc.) Quickstart Below, we provide simple exa
Problem torch.compile() shows an impressive ~2x speed-up for this code repo, but when applying to huggingface transformers there is barely no speed-up. I want to understand why, and then figure out how TorchInductor can also benefit HF m...
JW:It’s a common misperception that you need to run training and inference on the same models. It’s actually very easy to take one framework and run it on another piece of hardware. It’s particularly easy when you use [AI frameworks like]PyTorchandTensorflow; the models are extremely p...
and where it tripped up is exactly where I would have expected new students to get tripped up. That’s not to say it does perfect (or well) on Julia, but it clearly did better, and thus after trying hardI tended to only use ChatGPT to ...
Finally, I like to remind people that data science does not happen in a vacuum. SQL queries are self-contained and can be easily shared with colleagues. This fosterscollaborationand ensures that others can reproduce data cleaning steps without manual intervention. ...