Shortlink: goo.gl/wSuuS9
The github repository can be found at https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/data_generators/wikisum
Shortlink: goo.gl/wSuuS9
The github repository can be found at https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/data_generators/wikisum
Great work!
Hi peterjliu, any news about the progress ?
Eagerly awaiting the dataset, want to apply other techinques to compare with the results.
Hi peterjliu, I was wondering if there were any updates on the dataset availability? I'm hoping to do some reproducibility tests. Thanks!
Is this the data set that @lukaszkaiser is referencing in the Google Developers video here? https://youtu.be/O2UvKxaOH7c?t=637
If he's going to boast about it, it would seem to make sense to actually have it be available. It sounds like a great application of @commoncrawl data.
Hi folks, check out the updated link now. Thanks for the patience.
@rafaelbou @sai-prasanna @vedant @SHohentanner @leisurehippo @coventry @cyberandy @Diego999 @Legalamb77 @tfmorris
Mentioning folks who specifically expressed interest here.
Thank you for the share. I was wondering if it would be possible to store the preprocessed datasets on a local computer (after the preprocessing on the cloud) of it is too large ? Do you have an estimate of the necessary space ? 10 GB ? 100 GB ? 1 TB ?
Thank you for your help !
This looks really useful. I noticed that the pre-processed vocabs seem to be available in the gs://tensor2tensor-data/ bucket too (vocab.wikisum_commoncrawl.32768 and vocab.wikisum_web.32768)
The TODO says you release the hparams_set, which would be great, but can I request a pre-trained model release too?
Dear all,
Is there any available pre-trained model released for this wikisum problem? If there is, may I have the link to that pre-trained model?
Thank you so much
Thanks for linking that, @peterjliu. Am I reading the README.md
correctly, here, that training uses a full transformer architecture, rather than a decoder-only architecture with memory-compressed attention?
TODO(rsepassi): Put actual results achieved on wikisum_web
and/or
wikisum_commoncrawl
and with what hparams_set
.
PROBLEM=wikisum_web # or wikisum_commoncrawl
t2t-trainer \
--problem=$PROBLEM \
--model=transformer \
--hparams_set=transformer_base \
--train_steps=250000 \
--eval_steps=100 \
--data_dir=$DATA_DIR \
--output_dir=$TRAIN_DIR
Does anyone have processed training examples (i.e., the output of step 3 here) available to share? I'm having trouble getting GCP to release IP addresses for data generation, so I'm hoping to be able to bypass this for the time being...
Also, as @nlothian and @hoang-ho have asked, are pre-trained model weights available anywhere?
Thanks for letting me know.