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In testing the data upload feature, I mocked a dataset with ~20k rows in the header and ~100k rows in the episodes. The upload view took ~50 seconds to complete - I would expect this to timeout in pro…
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It should be possible to download larger datasets. To decide: when to do download and when to direct to github repo of data or other pre-compiled datasets? Should there be an upper limit to how much d…
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Thanks for your hard work. The hash implementation is amazing and outperforms many hash maps in C++.
By the way, do you guys have recommended settings with larger datasets (real industrial systems…
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Improve the package's efficiency when handling large datasets, focusing on speed and memory usage.
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Hi,
I’m working with an integrated Xenium dataset consisting of 12 samples, totaling approximately 5.4 million cells. After pre-processing the individual Xenium samples, I merged them into a single…
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> [!NOTE]
>
> I saw #2470 + a few other PRs and it looks like @tssweeney & co are already working on resolving this, but adding the issue as a +1 vote to that ongoing work.
This seems to be due…
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I have a large dataset of 300K images with different objects,car,human, animals, etc. Should I need to train from scratch or I can do transfer learning from your general pre-trained model?
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Hi,
thank you for the great package. I am trying to pre-build the graphs for some larger datasets that do not fit into RAM is this already possible (and also the training afterwards)?
best,
Jonatha…
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Hi,
excellent work you put into this package here!
I started using your package, but ran into some problems with a larger data set which is too big to load everything simultaneously into my memo…
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Is there any way to manage memory useage on large datasets? For example, when you're approaching ~40000 spots and ~10000 genes, memory use becomes huge. Is there a way to train seperate conditions, an…