* 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>
* see if unsloth installs cleanly in ci
* check unsloth install on regular tests, not sdist
* fix ampere check exception for ci
* use cached_property instead
* add an e2e test for unsloth qlora
* reduce seq len and mbsz to prevent oom in ci
* add checks for fp16 and sdp_attention
* pin unsloth to a specific release
* add unsloth to docker image too
* fix flash attn xentropy patch
* fix loss, add check for loss when using fa_xentropy
* fix special tokens for test
* typo
* test fa xentropy with and without gradient accum
* pr feedback changes
* fix 405b with lower cpu ram requirements
* make sure to use doouble quant and only skip output embeddings
* set model attributes
* more fixes for sharded fsdp loading
* update the base model in example to use pre-quantized nf4-bf16 weights
* upstream fixes for qlora+fsdp
* add support for optimi_adamw optimizer w kahan summation
* pydantic validator for optimi_adamw
* workaround for setting optimizer for fsdp
* make sure to install optimizer packages
* make sure to have parity for model parameters passed to optimizer
* add smoke test for optimi_adamw optimizer
* don't use foreach optimi by default
* support galore once upstreamed into transformers
* update module name for llama in readme and fix typing for all linear
* bump trl for deprecation fixes from newer transformers
* include galore as an extra and install in docker image
* fix optim_args type
* fix optim_args
* update dependencies for galore
* add galore to cicd dockerfile
* make mlflow optional
* fix xformers
don't patch swiglu if xformers not working
fix the check for xformers swiglu
* fix install of xformers with extra index url for docker builds
* fix docker build arg quoting
* wip modal for ci
* handle falcon layernorms better
* update
* rebuild the template each time with the pseudo-ARGS
* fix ref
* update tests to use modal
* cleanup ci script
* make sure to install jinja2 also
* kickoff the gh action on gh hosted runners and specify num gpus
* add a basic notebook for lab users in the root
* update notebook and fix cors for jupyter
* cell is code
* fix eval batch size check
* remove intro notebook
* attempt to also run e2e tests that needs gpus
* fix stray quote
* checkout specific github ref
* dockerfile for tests with proper checkout
ensure wandb is dissabled for docker pytests
clear wandb env after testing
clear wandb env after testing
make sure to provide a default val for pop
tryin skipping wandb validation tests
explicitly disable wandb in the e2e tests
explicitly report_to None to see if that fixes the docker e2e tests
split gpu from non-gpu unit tests
skip bf16 check in test for now
build docker w/o cache since it uses branch name ref
revert some changes now that caching is fixed
skip bf16 check if on gpu w support
* pytest skip for auto-gptq requirements
* skip mamba tests for now, split multipack and non packed lora llama tests
* split tests that use monkeypatches
* fix relative import for prev commit
* move other tests using monkeypatches to the correct run
* add torch to requirements.txt at build time to force version to stick
* fix xformers check
* better handling of xformers based on installed torch version
* fix for ci w/o torch
* mixtral multipack
* use mixtral model
* sample yml
* calculate cu_seqlens properly
* use updated flash ettention setting
* attn var checks
* force use of flash attention 2 for packing
* lint
* disable future fix for now
* update support table
* update readme to point to direct link to runpod template, cleanup install instrucitons
* default install flash-attn and auto-gptq now too
* update readme w flash-attn extra
* fix version in setup
* auto gptq support
* more tweaks and add yml
* remove old gptq docker
* don't need explicit peft install for tests
* fix setup.py to use extra index url
install torch for tests
fix cuda version for autogptq index
set torch in requirements so that it installs properly
move gptq install around to work with github cicd
* gptq doesn't play well with sample packing
* address pr feedback
* remove torch install for now
* set quantization_config from model config
* Fix the implementation for getting quant config from model config
