GitLab

* fix no sequence length models error

* block size check

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Co-authored-by: Adam Louly <adamlouly@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

fixed the broken links belogs to dataset library of transformers

fix max pos issue

Co-authored-by: Adam Louly <adamlouly@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

Add missing spaces in adjacent strings

* refactor: change default block_size

* fix: return tf to origin

* fix: change files to origin

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* refactor: add min block_size to files

* reformat: add min block_size for run_clm tf

* docs: add space to docs

* docs: remove reduntant space

* pytorch examples

* pytorch mim no trainer

* cookiecutter

* flax examples

* missed line in pytorch run_glue

* tensorflow examples

* tensorflow run_clip

* tensorflow run_mlm

* tensorflow run_ner

* tensorflow run_clm

* pytorch example from_configs

* pytorch no trainer examples

* Revert "tensorflow run_clip"

This reverts commit 261f86ac1f1c9e05dd3fd0291e1a1f8e573781d5.

* fix: duplicated argument

* fix

* fix

* fix

* fix

* fix

* fix

* fix

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

* pytorch examples

* tensorflow examples

* flax examples

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

Change logic

* fix bug in group_texts function, that was inserting short batches

* fully exclude short batches and return empty dict instead

* fix style

* add low_cpu_mem_usage option in run_clm.py example which will benefit LLM loading
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* update all the example and README under language-modeling
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Respect documentation on passive log level

* Fix test and set log level in examples

* Add doc

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* simplify column_names in run_clm

* simplify column_names in run_mlm

* minor

* [run_clm example] add streaming dataset support

* unrefactor kwargs

* fix

* fix

* require datasets>=2.0.0

* port to mlm

* [run_clm example] add torch_dtype option for model load.
for BLOOM 175B model. peak memory will reduce about 350G for inference. the weight of BLOOM in model hub is bfloat16
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add other type in option

* fix style
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Only resize embeddings when necessary

* Add comment

* zero chance anyone's using that constant no?

* `transformers-cli login` => `huggingface-cli login`

* `transformers-cli repo create` => `huggingface-cli repo create`

* `make style`

* Migrate metric to Evaluate in pytorch examples

* Remove unused imports