TechQA.

Question

Does using FP16 help accelerate generation? (HuggingFace BART)

score 910 · Answer 1 · 2020-09-28 12:16:34

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910

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Does using FP16 help accelerate generation? (HuggingFace BART)

910 views Asked by Allan-J At 28 September 2020 at 12:16

score 552 · Answer 2 · 2020-10-05 08:07:13

how does nn.embedding for developing an encoder-decoder model works?

552 views Asked by Kadaj13 At 05 October 2020 at 08:07

score 307 · Answer 3 · 2020-10-15 20:08:52

why seq2seq model return negative loss if I used a pre-trained embedding model

307 views Asked by Kamal El-Saaid At 15 October 2020 at 20:08

score 187 · Answer 4 · 2020-10-23 12:03:00

Is there a way for a closed domain chatbot to build using seq2seq, generative modeling or other methods like RNNs?

187 views Asked by jeff-ridgeway At 23 October 2020 at 12:03

score 136 · Answer 5 · 2023-10-29 08:40:47

Temporal Fusion Transformer model training encountered Gradient Vanishing

136 views Asked by Jack Lee At 29 October 2023 at 08:40

score 102 · Answer 6 · 2023-11-10 23:44:24

Training a transformer to copy sequence to identical sequence?

102 views Asked by pure At 10 November 2023 at 23:44

score 37 · Answer 7 · 2023-12-18 14:22:25

tensorflow multivariable seq 2 seq model return only lagged forcast

37 views Asked by Jonathan Roy At 18 December 2023 at 14:22

score 351 · Answer 8 · 2020-12-02 05:42:51

Error: Invalid argument: ConcatOp : Dimensions of inputs should match

351 views Asked by Terry At 02 December 2020 at 05:42

score 199 · Answer 9 · 2020-12-05 09:33:42

Transforming keras model output during training and use multiple losses

199 views Asked by Syed Rifat Mahmud Rafee At 05 December 2020 at 09:33

score 1204 · Answer 10 · 2020-12-16 03:15:07

LSTM seq2seq input and output with different number of time steps

1.2k views Asked by Kexin Wang At 16 December 2020 at 03:15

TechQA.

List Question

Does using FP16 help accelerate generation? (HuggingFace BART)

how does nn.embedding for developing an encoder-decoder model works?

why seq2seq model return negative loss if I used a pre-trained embedding model

Is there a way for a closed domain chatbot to build using seq2seq, generative modeling or other methods like RNNs?

Temporal Fusion Transformer model training encountered Gradient Vanishing

Training a transformer to copy sequence to identical sequence?

tensorflow multivariable seq 2 seq model return only lagged forcast

Error: Invalid argument: ConcatOp : Dimensions of inputs should match

Transforming keras model output during training and use multiple losses

LSTM seq2seq input and output with different number of time steps

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