GitLab

* Add initial remote hardware auto-setup docs

* Fix a few typos and clarify some language

* Add missing dependency

* Update self-hosted launch script with Sylvain's comments.

* Formatting.

* Trigger CI

* Style

missing None check

* First draft

* Fix integration test

* Remove script

* Fix test and typos

* Fix one more test

* Skip tied embeddings test

* Remove line

* Address comments

* Report safetensors version in transformers-cli env

* Styling

* Trigger CI maybe

for rg to be `False`

* seq2seq trainer and training arguments accepting GenerationConfig arg

* seq2seq Trainer and training arguments docstring fixes

* Update training_args_seq2seq.py docstring
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Fixing trainer_seq2seq.py docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* seq2seq trainer: legacy gen args back & GenerationConfig created at init

* Seq2seq trainer: fix in case gen_config.max_new_tokens is None
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* seq2seq trainer: adding legacy arg retrocompatibility

* seq2seq trainer and training arguments accepting GenerationConfig arg

* seq2seq Trainer and training arguments docstring fixes

* Update training_args_seq2seq.py docstring
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Fixing trainer_seq2seq.py docstring
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* seq2seq trainer: legacy gen args back & GenerationConfig created at init

* Seq2seq trainer: fix in case gen_config.max_new_tokens is None
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* seq2seq trainer: adding legacy arg retrocompatibility

* seq2seq trainer: evaluate and predict untouched

* Apply suggestions from code review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* seq2seq trainer: adding init args, keeping IDEs hints

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Wav2Vec2ProcessorWithLM can return N best hypotheses now
Signed-off-by: Vladislav Sokolovskii <vladislav@parrothq.com>

* Wav2Vec2ProcessorWithLM n_best cannot be None
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Batch decoding can return  N best hypotheses now

batch_decode was extended with the same functionality as decode
function, N best hypotheses per sample can be returned
Signed-off-by: Vladislav Sokolovskii <vladislav@parrothq.com>

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Signed-off-by: Vladislav Sokolovskii <vladislav@parrothq.com>
Co-authored-by: Vladislav Sokolovskii <vladislav@parrothq.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

balanced 8bit memory

* updated toctree

* added and translated mdx documents

Edited one line in src/transormers/generation/utils.py. Changed dist.world_size() to dist.get_world_size() since world_size() doesn't exist in pytorch.dist.

* missing cmake

* more cmake

* [safetensors] don't use in pt<1.10

* better fix

* [WIP] flax resnet

* added pretrained flax models, results reproducible

* Added pretrained flax models, results reproducible

* working on tests

* no real code change, just some comments

* [flax] adding support for batch norm layers

* fixing bugs related to pt+flax integration

* removing loss from modeling flax output class

* fixing classifier tests

* fixing comments, model output

* cleaning comments

* review changes

* review changes

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* renaming Flax to PyTorch

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Improve error message

* Fix consistency

* Pin tensorflow-text to go with tensorflow

* Make it more convenient to pin TensorFlow

* setup don't like f-strings

* update docker files to use official torch 2.0.0

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

* add mega file structure and plain pytorch version of mega source code

* added config class with old naming conventions

* filled in mega documentation

* added config class and embeddings with optional token types

* updated notes

* starting the conversion process, deleted intermediate and added use_cache back to config

* renamed config attributes in modeling_mega.py

* checkpointing before refactoring incremental decoding functions

* removed stateful incremental key/values for EMA and self-attention

* refactored MovingAverageGatedAttention to remove stateful k/v history and use unified attention mask

* MovingAverageGatedAttention works with incremental decoding + past values, added sequence length enforcement

* more comments in MovingAverageGatedAttention + checkpointing before GatedCrossAttention

* bug fix in attention mask handling in MovingAverageGatedAttention

* removed incremental state from GatedCrossAtt...

Fix typo in greedy search docs

* [HFTracer] Make embeddings ops take on the dtype of the weight

* fix bug

* Automatically create or update tiny models

* Skip failed tests

* update workflow file

* use revision

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

* Llama - Move target tokens to final pipeline device if needed

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

This PR fixes the "RuntimeError: No CUDA GPUs are available"
when running with --bf16 option on Neuron.

Related PRs:
https://github.com/huggingface/transformers/pull/20684
https://github.com/huggingface/transformers/pull/22300

* Added type hints to TFDeiTModel

* make style

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Co-authored-by: Matt <rocketknight1@gmail.com>

* Fix various imports

* Fix copies

* Fix import

* Mention why one needs to specify max_steps in Trainer

* dummy change to trigger CI

* Fixed gradient checkpoint bug for this model

* Updating PR indentation (maintainer feedback)

* make fixup

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Co-authored-by: younesbelkada <younesbelkada@gmail.com>

add `accelerate` support for MBart

* [gptj] support older pytorch version

* contributor

* contributor

* make copies

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Co-authored-by: Michael Wyatt <michaelwyatt@microsoft.com>
Co-authored-by: Nick Hill <nickhill@us.ibm.com>