GuitarLSTM

Deep learning models for guitar amp/pedal emulation using LSTM with Keras
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commit 753fe9c2f5519447a7c9ed5b19596a1af9751314
parent 1ecbeed0232d9c556ca455273a051eb37d94979b
Author: Keith Bloemer <32459398+GuitarML@users.noreply.github.com>
Date:   Sat,  5 Dec 2020 08:08:12 -0600

Update README.md
Diffstat:
MREADME.md | 7++++---
1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md @@ -88,9 +88,10 @@ Helpful tips on training models: This implementation of the LSTM model uses a high amount of RAM to preprocess wav data. If you experience crashes due to limited memory, reduce the "input_size" parameter by using -the "--input_size=" flag with train.py. The default setting is 100. -Increasing this setting will improve training accuracy, but the size -of the preprocessed wav data in RAM will increase as well. +the "--input_size=" flag with train.py. The default setting is 100, +which requires about 8GB of RAM. Increasing this setting will improve +training accuracy, but the size of the preprocessed wav data in +RAM will increase as well. Adding a custom dataloader would reduce RAM usage at the cost of training speed, and will be a focus of future work.