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* offline mode start

* add specific values

* fix fallback

* add test

* better values check and range

* test that actually works

* document the offline mode

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* more strict check

* cleaner test

* pt-only test

* style
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Refactor checkpoint name in ALBERT and ALBERT_tf

* Refactor checkpoint name in BART and BART_tf

* Refactor checkpoint name in BERT generation

* Refactor checkpoint name in Blenderbot_tf

* Refactor checkpoint name in Blenderbot_small_tf

* Refactor checkpoint name in ConvBERT AND CONVBERT_TF

* Refactor checkpoint name in CTRL AND CTRL_TF

* Refactor checkpoint name in DistilBERT AND DistilBERT_TF

* Refactor checkpoint name in DistilBERT redo

* Refactor checkpoint name in Electra and Electra_tf

* Refactor checkpoint name in FlauBERT and FlauBERT_tf

* Refactor checkpoint name in FSMT

* Refactor checkpoint name in GPT2 and GPT2_tf

* Refactor checkpoint name in IBERT

* Refactor checkpoint name in LED and LED_tf

* Refactor checkpoint name in Longformer and Longformer_tf

* Refactor checkpoint name in Lxmert and Lxmert_tf

* Refactor checkpoint name in Marian_tf

* Refactor checkpoint name in MBART and MBART_tf

* Refactor checkpoint name in MobileBERT and MobileBERT_tf

* Refactor checkpoint name in mpnet and mpnet_tf

* Refactor checkpoint name in openai and openai_tf

* Refactor checkpoint name in pegasus_tf

* Refactor checkpoint name in reformer

* Refactor checkpoint name in Roberta and Roberta_tf

* Refactor checkpoint name in SqueezeBert

* Refactor checkpoint name in Transformer_xl and Transformer_xl_tf

* Refactor checkpoint name in XLM and XLM_tf

* Refactor checkpoint name in XLNET and XLNET_tf

* Refactor checkpoint name in BERT_tf

* run make tests, style, quality, fixup

* Add stale bot to Github Actions

* Update message

* Message for assignee

* Update scripts/stale.py

* Uncomment & stop testing

* Fix embeddings for PyTorch 1.8

* Try with PyTorch 1.8.0

* Fix embeddings init

* Fix copies

* Typo

* More typos

DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST => DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST in line 31.

* Only run one test

* Patch segfault

* Fix summarization pipeline

* Ready for merge

* first step to refactor

* make all fast tests pass

* make all slow tests pass

* save intermediate

* correct cache

* finish PR

* make fp16 work

* Rework TPU checkpointing in Trainer

* Wraps the barrier in a dist test

* Address review comments

* Remove line

* removed overwrites

* remove default value for output_dir

* adjusted typing

This reverts commit f3660613.

* Fix gradient accumulation for SM Model Parallelism

* Style and divide loss by grad accum steps

* fix all_hidden_states

* use output_states instead of next_kv

* remap classes to strings

* missing new util

* style

* doc

* move the autogenerated file

* Trigger CI

* Refactor checkpoint name in BERT and MobileBERT

* Add option to check copies

* Add QuestionAnswering

* Add last models

* Make black happy

* feat(docs): navigate with left/right arrow keys

* fix: add missing comma

* fix speed degradation bug t5

* fix for all models

* fix code quality

Co-authored-by: WybeKoper <WybeKoper@users.noreply.github.com>

Changed `num_beams` to `num_beams // num_beam_groups` when initialising `PrefixConstrainedLogitsProcessor` in `_get_logits_processor` to fix compatibility issue when constrained decoding is used together with grouped beam search (#10475)

* smal fixes

* don't check for None

* add encode labels function to tokenizer

* start adding finetuning

* init dropout

* upload

* correct convert script

* apply changes

* fix second typo

* make first dummy training run

* adapt convert script

* push confg for comparison

* remove conf

* finish training

* adapt data collator

* add research folder

* update according to fairseq feedback

* some minor corrections

* refactor masking indices a bit

* some minor changes

* clean tokenizer

* finish clean-up

* remove previous logic

* update run script

* correct training

* finish changes

* finish model

* correct bug

* fix training a bit more

* add some tests

* finish gradient checkpointing

* finish example

* correct gradient checkpointing

* improve tokenization method

* revert changes in tokenizer

* revert general change

* adapt fine-tuning

* update

* save intermediate test

* Update README.md

* finish finetuning

* delete conversion script

* Update src/transformers/models/wav2vec2/configuration_wav2vec2.py

* Update src/transformers/models/wav2vec2/processing_wav2vec2.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* finish wav2vec2 script

* finish wav2vec2 fine-tuning

* finalize test

* correct test

* adapt tests

* finish

* remove test file
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* feat: Adds three definitions to glossary from @cronoik

Needed a definition for transformer which in turn needed 2 more definitions

To do with issue https://github.com/huggingface/transformers/issues/9078

* fix: Adjusts definition of neural network to make it easier to read

* Introduce save_strategy training argument

* deprecate EvaluationStrategy

* collapse EvaluationStrategy and LoggingStrategy into a single
  IntervalStrategy enum

* modify tests to use modified enum

* updated logging and saving metrics

* space removal

This PR restores the original functionality that for some reason was modified.

Fixes: https://github.com/huggingface/transformers/issues/10381

@sgugger