grph123dot

4 ms·

1.
by grph123dot 3y ago
Yesterday I asked chatgpt to compute the probability that two words of five letters both began with the same three letters and it could not solve it. It gave me about 10 different results but all were wrong, it seems the number five mislead
2.
by grph123dot 4y ago
Perhaps the concepts of vector embedding and the attention mechanism could be explained. Also you could use some prompts for LLM to generate new content for your intended audience, mostly to classify them, so that your reader could copy you
3.
by grph123dot 4y ago
The Alpaca lora result is incorrect since, for example, if all elements in array are the same the result in just an array with one element.
4.
by grph123dot 4y ago
>> that the change in the weights as you train also have low intrinsic rank It seems that the initial matrix of weights has a low rank approximation A and this implies that the difference E = W - A is small, also it seems that PCA fai
5.
by grph123dot 4y ago
Since we are in ELI5, it seems that the concept of low rank approximation is required to understand this method. (1) https://en.wikipedia.org/wiki/Low-rank_approximation Edited: By the way, it seems to me that there i
6.
by grph123dot 4y ago
Your explanation is crystal clear. I suppose it works well in practice, but is there any reason it works that well?
7.
by grph123dot 4y ago
I think that google could use a LLM with wxmaxima and some database, for example using maxima the LLM could show the source code used and perhaps it could adapt the code to new problems.