0.8M parameters model (16,000 times smaller than Vicuna-13B) training…#1
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avesus wants to merge 1 commit intoomnipresentalgorithm:much-simplerfrom
Open
0.8M parameters model (16,000 times smaller than Vicuna-13B) training…#1avesus wants to merge 1 commit intoomnipresentalgorithm:much-simplerfrom
avesus wants to merge 1 commit intoomnipresentalgorithm:much-simplerfrom
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… over 50,000 iterations makes wild stories
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A simple 4 layer generative Transformer with 16 attention heads.
One tweak of LLaMA is the embedding matrix, for which computed a pseudo-inverse used as unembedding that's being backpropagated.
After 50,000 iterations it generates wild tiny stories.
This PR adds an example of inference parameters and training (with example of run over 50,000 iterations).