Office space meme:
“If y’all could stop calling an LLM “open source” just because they published the weights… that would be great.”
Office space meme:
“If y’all could stop calling an LLM “open source” just because they published the weights… that would be great.”
Hey, I have trained several models in pytorch, darknet, tensorflow.
With the same dataset and the same training parameters, the same final iteration of training actually does return the same weights. There’s no randomness unless they specifically add random layers and that’s not really a good idea with RNNs it wasn’t when I was working with them at least. In any case, weights should converge into a very similar point even if randomness is introduced or else the RNN is pretty much worthless.
There’s usually randomness involved with the initial weights and the order the data is processed.