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Hi lopuhin.
Thanks for your sharing.
I used your model to predict the next word, but I found the forecast speed relatively slow, probably because of the lm.inference.get_log_probs function to predict the probability of all both words in sentences. Meanwhile, the problem of predicting the next word only requires the probability of the last word.
The text was updated successfully, but these errors were encountered:
Thanks for feedback. Did you find it slow compared to other similar models / implementations?
Meanwhile, the problem of predicting the next word only requires the probability of the last word.
Right. But we still need to process all previous words. I see that we could avoid doing softmax for all but the last word, not sure how much difference will it bring.
FWIW there is a big speedup in text generation here 4c18649 - this speeds up generation of multiple tokens, while the single token generation has the same speed.
Hi lopuhin.
Thanks for your sharing.
I used your model to predict the next word, but I found the forecast speed relatively slow, probably because of the lm.inference.get_log_probs function to predict the probability of all both words in sentences. Meanwhile, the problem of predicting the next word only requires the probability of the last word.
The text was updated successfully, but these errors were encountered: