Skip to content

Adds NLP example references. #1500

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
andsteing merged 1 commit into from
Aug 24, 2021
Merged

Adds NLP example references. #1500

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 13 additions & 4 deletions docs/examples.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,10 +35,19 @@ Natural language processing
- `Sequence to sequence for number
addition <https://github.com/google/flax/tree/main/examples/seq2seq/>`__
(featuring simple code, LSTM state handling, on the fly data generation).
- `Transformer model on
WMT <https://github.com/google/flax/tree/main/examples/wmt/>`__ :
Translating English/German (featuring multihost SPMD, dynamic bucketing, attention cache,
packed sequences, recipe for TPU training on GCP).
- `Parts-of-speech tagging
<https://github.com/google/flax/tree/main/examples/nlp_seq/>`__ : Simple
transformer encoder model using the universal dependency dataset.
- `Sentiment classification
<https://github.com/google/flax/tree/main/examples/sst2/>`__ :
with a LSTM model.
- `Transformer encoder/decoder model trained on WMT
<https://github.com/google/flax/tree/main/examples/wmt/>`__ :
Translating English/German (featuring multihost SPMD, dynamic bucketing,
attention cache, packed sequences, recipe for TPU training on GCP).
- `Transformer encoder trained on one billion word benchmark
<https://github.com/google/flax/tree/main/examples/lm1b/>`__ :
for autoregressive language modeling, based on the WMT example above.

Generative models

Expand Down