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Hello @syncdoth, great work !
I just wanted understand your view on the original paper. Do you think if this model is as powerful as authors of this paper claim it to be ? Did you find any issues w…
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test code:
```
retnet3=ggarg::read.beast("../data/retnet.nexus")
ggret(retnet3) #doesn't work
ggplot(retnet3) + geom_ret() #works
```
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Hi, Thanks for your great work. I ran benchmarks to test all modes' throughput and memory usage with code `flash-linear-attention/benchmarks/benchmark_training_throughput.py`. Some of them, unfortuna…
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but it works if the evonet object was extracted from a treedata object in the first place
example code:
```
#read retnet in newick format (creates an evonet object by default)
retnet.evonet = …
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have you seen this dataset? maybe it's better suited for zero-shot task, more natural speech than audiobook
https://github.com/open-mmlab/Amphion/blob/main/preprocessors/Emilia/README.md
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- https://www.nature.com/articles/s41591-021-01351-4
- 2021
オプトジェネティクスは、神経疾患におけるニューロンの機能を、変異に依存せず、回路特異的に回復させることを可能にするかもしれない。
網膜色素変性症は、光受容体が失われることで完全に失明してしまう神経変性眼疾患である。
私たちは、ChrimsonRをコードするアデノ随伴ウ…
e4exp updated
3 years ago
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A good job!
In addition to mamba, I would like to understand how xLSTM compares with other linear complexity models such as Vsion-RWKV and RetNet.
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When using groupClade() on a treedata object, It seems that all non terminal branches of the tree are included in the newly defined clade, e.g.:
```
retnet3=ggarg::read.beast("../data/retnet.nexus…