* feat: move to uv first
* fix: update doc to uv first
* fix: merge dev/tests into uv pyproject
* fix: update docker docs to match current config
* fix: migrate examples to readme
* fix: add llmcompressor to conflict
* feat: rec uv sync with lockfile for dev/ci
* fix: update docker docs to clarify how to use uv images
* chore: docs
* fix: use system python, no venv
* fix: set backend cpu
* fix: only set for installing pytorch step
* fix: remove unsloth kernel and installs
* fix: remove U in tests
* fix: set backend in deps too
* chore: test
* chore: comments
* fix: attempt to lock torch
* fix: workaround torch cuda and not upgraded
* fix: forgot to push
* fix: missed source
* fix: nightly upstream loralinear config
* fix: nightly phi3 long rope not work
* fix: forgot commit
* fix: test phi3 template change
* fix: no more requirements
* fix: carry over changes from new requirements to pyproject
* chore: remove lockfile per discussion
* fix: set match-runtime
* fix: remove unneeded hf hub buildtime
* fix: duplicate cache delete on nightly
* fix: torchvision being overridden
* fix: migrate to uv images
* fix: leftover from merge
* fix: simplify base readme
* fix: update assertion message to be clearer
* chore: docs
* fix: change fallback for cicd script
* fix: match against main exactly
* fix: peft 0.19.1 change
* fix: e2e test
* fix: ci
* fix: e2e test
* fix: explicit set workflow permission and move secrets to necessary
steps only
* fix: comment
* fix: more permission restrict
* chore: add read for pypi
* update setuptools so trl can be installed from main for nightlies
* run the nightly in the PR CI on change
* use range request, don't use cu129 in CI since it's not supported with AO
* run multigpu ci if CCE install script changes
* extend pytest-sdist timeout to 30 min for slow/flaky tests
* Also preload the cdn cache so it doesn't get stampeded
* fix yaml syntax
* missing fields
* can't pipe to dev/null
* Fix nightlies and add 2.10.0 to multi-gpu suite
* make torch 2.6.0 the default image
* fix tests against upstream main
* fix attribute access
* use fixture dataset
* fix dataset load
* correct the fixtures + tests
* more fixtures
* add accidentally removed shakespeare fixture
* fix conversion from unittest to pytest class
* nightly main ci caches
* build 12.6.3 cuda base image
* override for fix from huggingface/transformers#37162
* address PR feedback
* fix: update chat_template
* fix: handle gemma3 showing a lot of no content for turn 0
* fix: remove unknown config from examples
* fix: test
* fix: temporary disable gemma2 test
* fix: stop overwriting config.text_config unnecessarily
* fix: handling of set cache to the text_config section
* feat: add liger gemma support and bump liger to 0.5.5
* fix: add double use_cache setting
* fix: add support for final_logit_softcap in CCE for gemma2/3
* fix: set use_cache before model load
* feat: add missing layernorm override
* fix: handle gemma3 rmsnorm
* fix: use wrapper to pass dim as hidden_size
* fix: change dim to positional
* fix: patch with wrong mlp
* chore: refactor use_cache handling
* fix import issues
* fix tests.e2e.utils import
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* add 12.8.1 cuda to the base matrix
* use nightly
* bump deepspeed and set no binary
* deepspeed binary fixes hopefully
* install deepspeed by itself
* multiline fix
* make sure ninja is installed
* try with reversion of packaging/setuptools/wheel install
* use license instead of license-file
* try rolling back packaging and setuptools versions
* comment out license for validation for now
* make sure packaging version is consistent
* more parity across tests and docker images for packaging/setuptools
* fix build w pyproject to respect insalled torch version
* include in manifest
* disable duplicate code check for now
* move parser so it can be found
* add checks for correct pytorch version so this doesn't slip by again
* reduce test concurrency to avoid HF rate limiting, test suite parity
* make val_set_size smaller to speed up e2e tests
* more retries for pytest fixture downloads
* val_set_size was too small
* move retry_on_request_exceptions to data utils and add retry strategy
* pre-download ultrafeedback as a test fixture
* refactor download retry into it's own fn
* don't import from data utils
* use retry mechanism now for fixtures
* Fix broken CLI; remove duplicate metadata from setup.py
* Adding tests.yml CLI check
* updating
* remove test with requests to github due to rate limiting
---------
Co-authored-by: Dan Saunders <dan@axolotl.ai>
* feat: add cut_cross_entropy
* fix: add to input
* fix: remove from setup.py
* feat: refactor into an integration
* chore: ignore lint
* feat: add test for cce
* fix: set max_steps for liger test
* chore: Update base model following suggestion
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* chore: update special_tokens following suggestion
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* chore: remove with_temp_dir following comments
* fix: plugins aren't loaded
* chore: update quotes in error message
* chore: lint
* chore: lint
* feat: enable FA on test
* chore: refactor get_pytorch_version
* fix: lock cce commit version
* fix: remove subclassing UT
* fix: downcast even if not using FA and config check
* feat: add test to check different attentions
* feat: add install to CI
* chore: refactor to use parametrize for attention
* fix: pytest not detecting test
* feat: handle torch lower than 2.4
* fix args/kwargs to match docs
* use release version cut-cross-entropy==24.11.4
* fix quotes
* fix: use named params for clarity for modal builder
* fix: handle install from pip
* fix: test check only top level module install
* fix: re-add import check
* uninstall existing version if no transformers submodule in cce
* more dataset fixtures into the cache
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
* update actions version for node16 deprecation
* update pre-commit/action to use 3.0.1 for actions/cache@v4 dep
* update docker/setup-buildx-action too to v3
* feat: support new arg num_items_in_batch
* use kwargs to manage extra unknown kwargs for now
* upgrade against upstream transformers main
* make sure trl is on latest too
* fix for upgraded trl
* fix: handle trl and transformer signature change
* feat: update trl to handle transformer signature
* RewardDataCollatorWithPadding no longer has max_length
* handle updated signature for tokenizer vs processor class
* invert logic for tokenizer vs processor class
* processing_class, not processor class
* also handle processing class in dpo
* handle model name w model card creation
* upgrade transformers and add a loss check test
* fix install of tbparse requirements
* make sure to add tbparse to req
* feat: revert kwarg to positional kwarg to be explicit
---------
Co-authored-by: Wing Lian <wing.lian@gmail.com>
