GitLab

* fix

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

* move code to Trainer.evaluate to enable use of that function with multiple datasets

* test

* update doc string

* and a tip

* forgot the type

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Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>

* add attention_bias hparam for a model trained without attention biases

* fix argument documentation error

* fix fa2

* fix FA2 for popular models

* improve warning and add Younes as co-author
Co-Authored-By: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix the warning

* Add Tip

* typo fix

* nit

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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

Signed-off-by: Abolfazl Shahbazi <abolfazl.shahbazi@intel.com>

Fix mistral link in mixtral.md

In docstring for PreTrainedModel.resize_token_embeddings, correct definition of new_num_tokens parameter to read "the new number of tokens" (meaning the new size of the vocab) rather than "the number of new tokens" (number of newly added tokens only).

* default config should not use sliding window

* update the doc

* nits

* add a proper test

* update

* update

* update expected value

* Update src/transformers/tokenization_utils_fast.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* convert to float

* average then N**2

* comment

* revert nit

* good to fo

* fixup

* Update tests/models/mixtral/test_modeling_mixtral.py
Co-authored-by: Lysandre Debut <hi@lysand.re>

* revert unrelated change

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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>

* speculative decoding

* fix test

* space

* better comments

* remove redundant test

* test nit

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

* PR comments

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

* When save a model, make a copy to be moved to CPU, dont move the original
model

* make deepcopy inside of _save_tpu

* Move to tpu without copy

Fix token link

* doc fix friday

* deprecated objects

* update not_doctested

* update toctree

Update semantic_segmentation.md

* More build_in_name_scope()

* Make sure we set the save spec now we don't do it with dummies anymore

* make fixup

remove warning if DISABLE_TELEMETRY is used

* Disable jitter noise during evaluation

* Update outdated configuration information

* Formatting

* Add new line

to reduce the storage size and also save the time of checkpoint saving while using deepspeed for training
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

Update mixtral.md

correct minor typo in overview

add SDPA into llava

* edits to _prepare_4d_causal_attention_mask()

* initial tests for 4d mask

* attention_mask_for_sdpa support

* added test for inner model hidden

* added autotest decorators

* test mask dtype to torch.int64

* torch.testing.assert_close
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* torch_device and @torch_gpu in tests

* upd tests

* +torch decorators

* torch decorators fixed

* more decorators!

* even more decorators

* fewer decorators

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix resuming from ckpt when suing FSDP with FULL_STATE_DICT

* update tests

* fix tests

* mps docs

* toctree

* first draft

* add to toctree

* edits

* feedback

* Update vipllava.md

* Update modeling_vipllava.py

* Fix wrong examples in llava usage.

* Update modeling_llava.py

Fix `low_cpu_mem_usage` Flag Conflict with DeepSpeed Zero 3 in `from_pretrained` for Models with `keep_in_fp32_modules`" (#27762)

Fix `from_pretrained` Logic
for `low_cpu_mem_usage` with DeepSpeed Zero3

* fix hf-internal-testing/fixtures_image_utils

* fix test

* comments

* add multi-node traning setting

* fix style

* make torch.load a bit safer

* Fixes

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Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Put device in tensor constructor instead of to()

* Fix copy

Add past_key_values to _skip_keys_device_placement  for LLaVa

* skip test from SpeechInput

* refine description of skip

* Update convert_mixtral_weights_to_hf.py

* forward contrib credits from original fix

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Co-authored-by: thomasw21 <thomasw21@users.noreply.github.com>