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Hi there. I want to understand how to use the RetNet to train a model with the longer context. It is not clear from available documentation how to train the model for a large context. There is no para…
pkpro updated
9 months ago
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Can you please point me to the dataset used to test this model ?
Thank you in advance
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It's an excellent work! Your implementation of RMT is truly impressive!
Nevertheless, I have a couple of questions regarding the code implementation. Was the "1D to 2D" and the "Decomposed ReSA in E…
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The error message says it misses the x and y aes, so probably affecting other functions. It works with ggret so maybe one could just stick to using this but then maybe remove geom_ret from the package…
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Test code:
```
retnet = read.enewick("../data/retnet.nwk")
ggret(data = retnet,retcol = "red") + theme_tree() #this doesn't work
ggplot(retnet) + geom_ret(retcol = "red") + theme_tree()#this wor…
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![image](https://github.com/syncdoth/RetNet/assets/902005/8eef7829-88ae-49e1-a65f-cd882268e688)
Trying to compare with other transformer architectures. But as soon as the training starts, the gradi…
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## Why
Machine Learning 輪講は最新の技術や論文を追うことで、エンジニアが「技術で解決できること」のレベルをあげていくことを目的にした会です。
prev.https://github.com/wantedly/machine-learning-round-table/issues/210
## What
話したいことがある人はここにコメントしましょう!…
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Great work!
It appears that both GLA and RetNet are optimized only for causal cases. Is there an optimized linear attention for non-causal scenarios?
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The unspecified lineages are marked as "Undefined" in the first case and NA in the second.
Maybe accord and or add an option to specify what value unspecified lineages should take? This is quite mi…
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Maybe read.beast.retnet or so? To avoid confusion with the treeio function