GitLab

* ready for PR

* cleanup

* correct FSMT_PRETRAINED_MODEL_ARCHIVE_LIST

* fix

* perfectionism

* revert change from another PR

* odd, already committed this one

* non-interactive upload workaround

* backup the failed experiment

* store langs in config

* workaround for localizing model path

* doc clean up as in https://github.com/huggingface/transformers/pull/6956



* style

* back out debug mode

* document: run_eval.py --num_beams 10

* remove unneeded constant

* typo

* re-use bart's Attention

* re-use EncoderLayer, DecoderLayer from bart

* refactor

* send to cuda and fp16

* cleanup

* revert (moved to another PR)

* better error message

* document run_eval --num_beams

* solve the problem of tokenizer finding the right files when model is local

* polish, remove hardcoded config

* add a note that the file is autogenerated to avoid losing changes

* prep for org change, remove unneeded code

* switch to model4.pt, update scores

* s/python/bash/

* missing init (but doesn't impact the finetuned model)

* cleanup

* major refactor (reuse-bart)

* new model, new expected weights

* cleanup

* cleanup

* full link

* fix model type

* merge porting notes

* style

* cleanup

* have to create a DecoderConfig object to handle vocab_size properly

* doc fix

* add note (not a public class)

* parametrize

* - add bleu scores integration tests

* skip test if sacrebleu is not installed

* cache heavy models/tokenizers

* some tweaks

* remove tokens that aren't used

* more purging

* simplify code

* switch to using decoder_start_token_id

* add doc

* Revert "major refactor (reuse-bart)"

This reverts commit 226dad15ca6a9ef4e26178526e878e8fc5c85874.

* decouple from bart

* remove unused code #1

* remove unused code #2

* remove unused code #3

* update instructions

* clean up

* move bleu eval to examples

* check import only once

* move data+gen script into files

* reuse via import

* take less space

* add prepare_seq2seq_batch (auto-tested)

* cleanup

* recode test to use json instead of yaml

* ignore keys not needed

* use the new -y in transformers-cli upload -y

* [xlm tok] config dict: fix str into int to match definition (#7034)

* [s2s] --eval_max_generate_length (#7018)

* Fix CI with change of name of nlp (#7054)

* nlp -> datasets

* More nlp -> datasets

* Woopsie

* More nlp -> datasets

* One last

* extending to support allen_nlp wmt models

- allow a specific checkpoint file to be passed
- more arg settings
- scripts for allen_nlp models

* sync with changes

* s/fsmt-wmt/wmt/ in model names

* s/fsmt-wmt/wmt/ in model names (p2)

* s/fsmt-wmt/wmt/ in model names (p3)

* switch to a better checkpoint

* typo

* make non-optional args such - adjust tests where possible or skip when there is no other choice

* consistency

* style

* adjust header

* cards moved (model rename)

* use best custom hparams

* update info

* remove old cards

* cleanup

* s/stas/facebook/

* update scores

* s/allen_nlp/allenai/

* url maps aren't needed

* typo

* move all the doc / build /eval generators to their own scripts

* cleanup

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* fix indent

* duplicated line

* style

* use the correct add_start_docstrings

* oops

* resizing can't be done with the core approach, due to 2 dicts

* check that the arg is a list

* style

* style
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>