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transformers/examples/research_projects
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Patrick von Platen da9754a3a0
[Flax] Align jax flax device name (#12987) 
* [Flax] Align device name in docs

* make style

* fix import error
2021-08-04 16:00:09 +02:00
..
adversarial remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
bert-loses-patience remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
bertabs make style (#11442) 2021-04-26 13:50:34 +02:00
bertology [style] consistent nn. and nn.functional: part 4 examples (#12156) 2021-06-14 12:28:24 -07:00
deebert remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
distillation Fix distiller.py (#12910) 2021-07-29 02:11:38 +08:00
jax-projects [Flax] Align jax flax device name (#12987) 2021-08-04 16:00:09 +02:00
longform-qa [style] consistent nn. and nn.functional: part 4 examples (#12156) 2021-06-14 12:28:24 -07:00
lxmert [style] consistent nn. and nn.functional: part 4 examples (#12156) 2021-06-14 12:28:24 -07:00
mlm_wwm remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
mm-imdb remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
movement-pruning remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
performer remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
pplm [style] consistent nn. and nn.functional: part 4 examples (#12156) 2021-06-14 12:28:24 -07:00
rag minor fixes in original RAG training (#12395) 2021-06-29 13:39:48 +01:00
rag-end2end-retriever rm require_version_examples (#12088) 2021-06-09 11:02:52 -07:00
seq2seq-distillation Fix for making student ProphetNet for Seq2Seq Distillation (#12130) 2021-06-21 09:36:44 -04:00
wav2vec2 fix typo in gradient_checkpointing arg (#12855) 2021-07-30 15:06:33 +08:00
zero-shot-distillation remove extra white space from log format (#12360) 2021-06-25 13:20:14 -07:00
README.md Reorganize examples (#9010) 2020-12-11 10:07:02 -05:00

README.md

Research projects

This folder contains various research projects using 🤗 Transformers. They are not maintained and require a specific version of 🤗 Transformers that is indicated in the requirements file of each folder. Updating them to the most recent version of the library will require some work.

To use any of them, just run the command

pip install -r requirements.txt

inside the folder of your choice.

If you need help with any of those, contact the author(s), indicated at the top of the README of each folder.