* update trl to 0.17.0
* grpo + vllm no longer supported with 2.5.1 due to vllm constraints
* disable VLLM_USE_V1 for ci
* imporve handle killing off of multiprocessing vllm service
* debug why this doesn't run in CI
* increase vllm wait time
* increase timeout to 5min
* upgrade to vllm 0.8.4
* dump out the vllm log for debugging
* use debug logging
* increase vllm start timeout
* use NVL instead
* disable torch compile cache
* revert some commented checks now that grpo tests are fixed
* increase vllm timeoout back to 5min
* fixes for delinearization, and make qlora work with fsdp2
* Add back mistakenly removed lm_eval
* typo [skip ci]
* patch evals for torch.compile + fsdp2
* also check torch_compile w fsdp2
* lots of fixes for flex attn with llama4
* fix patch check and patch llama4 too
* attempt to make the patches stick
* use transformers 4.51.2
* update configs and README for llama4
* remove torch.compile for CI test
* cleanup any existing singletons
* set singleton cache to None instead of deleting
* use importlib reload with monkeypatch
* don't worry about transformers version, mark inputs with grads, fix regex
* make sure embeds aren't on cpu
* logging and mem improvements
* vllm version and add to docker, make sure to save processor on conversion
* fix ambiguous tensor bool check
* fix vllm to not use v1, upgrade hf transformers
* fix tests
* make flex_attn_compile_kwargs configurable, since this depends on model params
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: Salman Mohammadi <salman.mohammadi@outlook.com>
* llama4 support
* add xet support [skip ci]
* be flexible on transformers version and skip test on version
* don't use deepspeed for the fix_untrained_tokens test
* reordering to trigger torch 2.6.0 tests first
* slightly smaller train set
* use 4.51.0 for now
* remove stray print, add llama4 chat template to schema, bump peft to 0.15.1
* patches to make llama4 performant
* add preliminary fp8 support
* fsdp2 support
* use accelerate release 1.6.0
* allow 8bit optims with fsdp2
* liger + torch compile fix
* add fsdp2 e2e tests
* use transformers commit with fsdp2 support
* skip zero3 tests for this PR for now
* fix fsdp2 config for ci
* make sure both flex and flash attn work with fsdp2, skip fix untrained tokens
* okay, actually use fdsp2...
* more fixes to flex for fsdp2
* make sure to patch all the loaded models
* additional validation for fsdp2, bump dep versions
* 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
* add grpo scale_rewards config for trl#3135
* options to connect to vllm server directly w grpo trl#3094
* temperature support trl#3029
* sampling/generation kwargs for grpo trl#2989
* make vllm_enable_prefix_caching a config param trl#2900
* grpo multi-step optimizeations trl#2899
* remove overrides for grpo trainer
* bump trl to 0.16.0
* add cli to start vllm-serve via trl
* call the python module directly
* update to use vllm with 2.6.0 too now and call trl vllm serve from module
* vllm 0.8.1
* use python3
* use sys.executable
* remove context and wait for start
* fixes to make it actually work
* fixes so the grpo tests pass with new vllm paradigm
* explicit host/port and check in start vllm
* make sure that vllm doesn't hang by setting quiet so outouts go to dev null
* also bump bnb to latest release
* add option for wait from cli and nccl debugging for ci
* grpo + vllm test on separate devices for now
* make sure grpo + vllm tests runs single worker since pynccl comms would conflict
* fix cli
* remove wait and add caching for argilla dataset
* refactoring configs
* chore: lint
* add vllm config
* fixup vllm grpo args
* fix one more incorrect schema/config path
* fix another vlllm reference and increase timeout
* make the tests run a bit faster
* change mbsz back so it is correct for grpo
* another change mbsz back so it is correct for grpo
* fixing cli args
* nits
* adding docs
* docs
* include tensor parallel size for vllm in pydantic schema
* moving start_vllm, more docs
* limit output len for grpo vllm
* vllm enable_prefix_caching isn't a bool cli arg
* fix env ordering in tests and also use pid check when looking for vllm
---------
Co-authored-by: Salman Mohammadi <salman.mohammadi@outlook.com>
* hf offline decorator for tests to workaround rate limits
* fail quicker so we can see logs
* try new cache name
* limit files downloaded
* phi mini predownload
* offline decorator for phi tokenizer
* handle meta llama 8b offline too
* make sure to return fixtures if they are wrapped too
* more fixes
* more things offline
* more offline things
* fix the env var
* fix the model name
* handle gemma also
* force reload of modules to recheck offline status
* prefetch mistral too
* use reset_sessions so hub picks up offline mode
* more fixes
* rename so it doesn't seem like a context manager
* fix backoff
* switch out tinyshakespeare dataset since it runs a py script to fetch data and doesn't work offline
* include additional dataset
* more fixes
* more fixes
* replace tiny shakespeaere dataset
* skip some tests for now
* use more robust check using snapshot download to determine if a dataset name is on the hub
* typo for skip reason
* use local_files_only
* more fixtures
* remove local only
* use tiny shakespeare as pretrain dataset and streaming can't be offline even if precached
* make sure fixtures aren't offline
improve the offline reset
try bumping version of datasets
reorder reloading and setting
prime a new cache
run the tests now with fresh cache
try with a static cache
* now run all the ci again with hopefully a correct cache
* skip wonky tests for now
* skip wonky tests for now
* handle offline mode for model card creation
* 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
* use default torch fused adamw optimizer as default as adamw_hf is deprecated
* make sure to have latest packaging installed
* bump packagingin requirements.txt too
* pass additional info for fix untrained tokens when using distributed + offloading
* use latest version of vendored lib
* use v0.0.5 of contribs lgpl
* fix for no bad tokens and add tests
* use release
* add multigpu test too
* make sure the multigpu zero3 test actually uses zero3
* add muon optimizer
optimizer_cls_and_kwargs is on trainer_kwargs
only add adamw_kwargs if they're non-null
fix mocks
better handling of override and check the optimizer
unwrap optimizer
* fix import
* native support for modal cloud from CLI
* do lm_eval in cloud too
* Fix the sub call to lm-eval
* lm_eval option to not post eval, and append not extend
* cache bust when using branch, grab sha of latest image tag, update lm-eval dep
* allow minimal yaml for lm eval
* include modal in requirements
* update link in README to include utm
* pr feedback
* use chat template
* revision support
* apply chat template as arg
* add wandb name support, allow explicit a100-40gb
* cloud is optional
* handle accidental setting of tasks with a single task str
* document the modal cloud yaml for clarity [skip ci]
* cli docs
* support spawn vs remote for lm-eval
* Add support for additional docker commands in modal image build
* cloud config shouldn't be a dir
* Update README.md
Co-authored-by: Charles Frye <cfrye59@gmail.com>
* fix annotation args
---------
Co-authored-by: Charles Frye <cfrye59@gmail.com>
* transformers 4.47.1
* drop monkeypatches
* can't remove patches yet
* make flash attention forward ignore the loss kwargs
* patch the flash attention in the modeling arch too
* remove fsdp and deepspeed patches
* cleanup PR
* bump accelerate and torchao, also logically reorder/group requirements
* meant to include torchao
* use official patch release
* allow flexibility in transformers version for FSDP
* more flexibility with dev versions of 4.47.0.dev0
* add patch for fsdp
* fix typo
* correct fn name
* stray character
* fix patch
* reset Trainer too
* also reset Trainer.training_step
* allow tests/patched to run more than one process on e2e runner
* skip tests/patched in e2e for now since it's run in regular pytest
* bump transformers and trl
* fix: update trainer.log signature
* fix trl trainer.log interfaces
* broken 🦥 with latest transformers
* skip parent, call grandparent - yeah, super janky
* update HF HUB env var and fix reward trainer log since it doesn't directly override log
* also bump accelerate
* patches for llama ga
* detab the code to check
* fix whitespace for patch check
* play nicely with CI tests since we patch everytime
* fix pop default in case it doesn't exist
* more tweaks to make patches nicer in CI
* fix detab for when there are possibly multiple patches
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* add mhenrichsen/alpaca_2k_test with revision dataset download fixture for flaky tests
* log slowest tests
* pin pynvml==11.5.3
* fix load local hub path
* optimize for speed w smaller models and val_set_size
* replace pynvml
* make the resume from checkpoint e2e faster
* make tests smaller
* point to upstream autoawq for transformers fix
* use autoawq 0.2.7 release
* test wheel for awq
* try different format for wheel def
* autoawq re-release
* Add intel_extension_for_pytorch dep
* ipex gte version
* forcefully remove intel-extension-for-pytorch
* add -y option to pip uninstall for ipex
* use post2 release for autoawq and remove uninstall of ipex
