Difference between revisions of "RNNs with Darknet"
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wget https://pjreddie.com/media/files/tolstoy.weights | wget https://pjreddie.com/media/files/tolstoy.weights | ||
| − | *Generating | + | *Example: Generating a text based on the pre-trained model with books written by Shakespeare with Darknet: |
| + | *The machine learning framework ''Darknet'', is installed in the black PCs of the Interaction Station. We will use the operating system Ubuntu (Linux): | ||
| + | *Login & password: interactionstation | ||
| + | *We first need to open the terminal | ||
| + | *Then we need to go to the darknet directory. Try typing ''cd darknet'' and press the Enter key. In some computers is installed in another directory and you need to type cd /media/Machine_Learning/darknet: | ||
| + | *Then we are going to type: | ||
./darknet rnn generate cfg/rnn.cfg shakespeare.weights -srand 0 | ./darknet rnn generate cfg/rnn.cfg shakespeare.weights -srand 0 | ||
*Parameters: | *Parameters: | ||
| − | -srand N -> N determines the random seed | + | -srand N -> N determines the random seed. To be able to generate new texts, instead of 0 use another number. |
| − | + | '''Training with other corpus of text''' | |
*Download a text file. Some corpus of text online: | *Download a text file. Some corpus of text online: | ||
| Line 33: | Line 38: | ||
./darknet rnn generate cfg/rnn.cfg filename.weights -srand 0 | ./darknet rnn generate cfg/rnn.cfg filename.weights -srand 0 | ||
| + | *Parameters: | ||
| + | -srand N -> N determines the random seed. To be able to generate new texts, instead of 0 use another number. | ||
*Optional: We can modify file cfg/rnn.train.cfg file (batch = 50 is the value we set by default, the original value was 256) | *Optional: We can modify file cfg/rnn.train.cfg file (batch = 50 is the value we set by default, the original value was 256) | ||
| Line 38: | Line 45: | ||
*More info: | *More info: | ||
*https://pjreddie.com/darknet/rnns-in-darknet/ | *https://pjreddie.com/darknet/rnns-in-darknet/ | ||
| + | |||
Terminal basic tutorial: https://maker.pro/linux/tutorial/basic-linux-commands-for-beginners | Terminal basic tutorial: https://maker.pro/linux/tutorial/basic-linux-commands-for-beginners | ||
Revision as of 18:56, 15 April 2019
Installing Darknet
- We need to install our modified version of Darknet:
- Darknet Installation
Using RNNs with Darknet
- Getting some calculated weights from several writers:
wget https://pjreddie.com/media/files/shakespeare.weights wget https://pjreddie.com/media/files/kant.weights wget https://pjreddie.com/media/files/tolstoy.weights
- Example: Generating a text based on the pre-trained model with books written by Shakespeare with Darknet:
- The machine learning framework Darknet, is installed in the black PCs of the Interaction Station. We will use the operating system Ubuntu (Linux):
- Login & password: interactionstation
- We first need to open the terminal
- Then we need to go to the darknet directory. Try typing cd darknet and press the Enter key. In some computers is installed in another directory and you need to type cd /media/Machine_Learning/darknet:
*Then we are going to type: ./darknet rnn generate cfg/rnn.cfg shakespeare.weights -srand 0
- Parameters:
-srand N -> N determines the random seed. To be able to generate new texts, instead of 0 use another number.
Training with other corpus of text
- Download a text file. Some corpus of text online:
George Meredith http://www.gutenberg.org/ebooks/4500 Mark Twain http://www.gutenberg.org/ebooks/3200 More http://www.gutenberg.org/ebooks/search/?query=The+Complete+Works+of
- We train the neural network with the new text (This might take a while):
./darknet rnn train cfg/rnn.train.cfg -file filename.txt
- Generating new text with our new model
./darknet rnn generate cfg/rnn.cfg filename.weights -srand 0
- Parameters:
-srand N -> N determines the random seed. To be able to generate new texts, instead of 0 use another number.
- Optional: We can modify file cfg/rnn.train.cfg file (batch = 50 is the value we set by default, the original value was 256)
Terminal basic tutorial: https://maker.pro/linux/tutorial/basic-linux-commands-for-beginners