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Thank so much for your code, its helping me in my project.
But I am facing a small issue not sure if we can fix it or not:
I am embedding (using XLNET) 3 inputs each input has 5400 sentences and each sentence has 20 words
so the total is 3 * 5400 * 20
2 hours has passed till now and it still didn't finish embedding the first input (5400 *20)
I think I will run out of memory in Google Colab as well before finishing the embedding part [ofcourse this happened 🙈 it didn't even finish embedding the 1st input]
I notice that with each embedding its printing
"Converting texts to features: 100%|██████████| 20/20 [00:00<00:00, 17637.95it/s]INFO:tensorflow:memory input None
INFO:tensorflow:Use float type <dtype: 'float32'>"
is it possible to avoid printing that line with each embedding to speed up the process ?
The text was updated successfully, but these errors were encountered:
Thank so much for your code, its helping me in my project.
But I am facing a small issue not sure if we can fix it or not:
I am embedding (using XLNET) 3 inputs each input has 5400 sentences and each sentence has 20 words
so the total is 3 * 5400 * 20
2 hours has passed till now and it still didn't finish embedding the first input (5400 *20)
I think I will run out of memory in Google Colab as well before finishing the embedding part [ofcourse this happened 🙈 it didn't even finish embedding the 1st input]
I notice that with each embedding its printing
is it possible to avoid printing that line with each embedding to speed up the process ?
The text was updated successfully, but these errors were encountered: