Comments (2)
Vincent-ch99
commented on June 26, 2024
Yeh, I met the same situation like u
I loaded the embeddings and passages of precomputing, but when I run evaluate.py, it always shows cuda out of memory while loading. I have an A100 80G GPU memory. How much GPU memory is needed at least to load the precomputing embedding?
And I also encountered the problem of extremely slowly loading. Is there any way to optimize it?
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xudongguan202
commented on June 26, 2024
@Vincent-ch99
At least 2x A100 80G GPUs are required to run the evaluation using the default configurations from my experiment.
The extremely slow loading could be due to index compression of saved index, as mentioned in the paper. Therefore, I am currently trying to find a way to save and load the compressed index for faster loading and light storage.
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