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takeraparterer

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replied to TuringsSolutions's post about 10 hours ago
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replied to TuringsSolutions's post about 11 hours ago
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replied to TuringsSolutions's post about 13 hours ago
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replied to TuringsSolutions's post about 14 hours ago
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I think you should add dropout or decrease the size of the model

replied to TuringsSolutions's post about 14 hours ago
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I think your model is overfitting you should add dropout or decrease the size of it

replied to TuringsSolutions's post about 14 hours ago
replied to TuringsSolutions's post about 15 hours ago
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You should try dropout or decreasing the model size

replied to TuringsSolutions's post 1 day ago
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What about test loss? It looks like overfitting to me.

replied to TuringsSolutions's post 1 day ago
upvoted an article 3 days ago
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Article

Understanding the Algorithm of Thoughts: A Heuristic Approach Beyond LLMs

By TuringsSolutions โ€ข
โ€ข 2
replied to TuringsSolutions's post 6 days ago
replied to their post 7 days ago
replied to TuringsSolutions's post 7 days ago
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image.png
that's a FFN, which is only a small part of an LLM

Reacted to TuringsSolutions's post with ๐Ÿ˜” 7 days ago
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What if I told you that LLM models do not simply predict the next token in a sequence but instead utilize an emergent structural pattern-based system to comprehend language and concepts? I created a graph-based optimizer that not only works, but it also actually beats Adam, like very badly. I prove it thoroughly using SMOL LLM models. The secret? The graph is not what you think it is, humans. Code, full explanation, and more in this video. The Rhizome Optimizer is MIT licensed. I have completed my research. I fully understand now.

https://youtu.be/OMCRRueMhdI
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ยท
replied to TuringsSolutions's post 16 days ago
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has threatened violence in subtle ways

๐Ÿ˜ญ๐Ÿ˜ญ๐Ÿ˜ญ๐Ÿ˜ญ๐Ÿ˜ญ๐Ÿ˜ญ

replied to TuringsSolutions's post 16 days ago
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very intriguing. looking into this ๐Ÿ‘€๐Ÿ‘€๐Ÿ‘€

replied to TuringsSolutions's post 16 days ago