After attention, a simple feed-forward network (two linear layers with ReLU or GELU) processes each token independently. This is where most of the model’s parameters live.
if == " main ": train()
This feature is targeted at:
End of write-up.
Build a Large Language Model (From Scratch) - Sebastian Raschka
Result: A "Foundation Model" that understands language but can't follow instructions yet. :
After attention, a simple feed-forward network (two linear layers with ReLU or GELU) processes each token independently. This is where most of the model’s parameters live.
if == " main ": train()
This feature is targeted at:
End of write-up.
Build a Large Language Model (From Scratch) - Sebastian Raschka
Result: A "Foundation Model" that understands language but can't follow instructions yet. :
