* build examples readmes with quarto
* chore: formatting
* feat: dynamic build docs
* feat: add more model guides
* chore: format
* fix: collapse sidebar completely to have space for model guides
* fix: security protection for generated qmd
* fix: adjust collapse level, add new models, update links
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* Add support for Dion optimizer
* dion training kwargs
* fix var names
* no dion 8bit for now
* use updated axolotl-contribs-mit for dion optimizer
* add smoke test for dion optimizer
* add docs
* fix typo during edits
* fix test to not remove load in 8bit
* jagged lr restart scheudler
var name fix
make sure to create scheduler first
* wire things together
* more fixes
* fix for nesting scheduler and first anneal phase
* no need for relora trainer anymore since we've generalized the relora scheduler
* remove redundant relora scheduler and lint
* update relora e2e test for updated params
* need restart steps for relora test
* update quarto docs for dropped relora trainer
* update example yaml
* drop verbose arg
* min lr scale support for jagged lr
* don't let min_lr be nonetype
* cleanup args
* use cuda streams for activation offloading
* use torch native ops
* update cfg schema for streams
* fix literal constructor for set
* use context for training step so it doesn't affect evals
* disable streams
* auto gc on eval steps
* use activation_offloading config arg
* add docs for gradient checkpointing
* handle validation for gc/ao
* use cuda streams for act offloading
* add more validation for AC w/o GC
* fix docs
* move activation_offloading lower in definition so it doesn't break args/kwargs
* fix kd due to import order
* bump hf deps
* upgrade liger-kernel too
* install cce from fork for transformers fix
* fix reference to vocab size in gemma3 patch
* use padding_idx instead of pad_token_id
* remove fixed gemma3 patch
* use updated cce fork
* fix local mllama cce patches w docstring
* add test for multipack with trainer setup and fix trainer for trainer refactor upstream
* bump modal version
* guard for iterable datasetS
* mllama model arch layout changed in latest transformers
* fix batch sampler with drop_last
* fix: address upstream vlm changes for lora
* fix: update references to old lora target path
* fix: remove mllama fa2 patch due to upstream fix
* fix: lora kernel patch path for multimodal models
* fix: removed mllama from quarto
* run test for came optim on 2.6.0+
* fix fsdp2 patch and remove deprecated patch
* make sure to set sequence_parallel_degree for grpo
* Add SP test for GRPO
* add sp to grpo config for trainer
* use reward_funcs as kwarg to grpo trainer
* fix the comprehension for reward funcs
* reward funcs already passed in as args
* init sp_group right before training
* fix check for adding models to SP context
* make sure to pass args to super
* upgrade deepspeed
* use updated trl and add reasoning flags for vllm
* patch the worker
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* feat: add num_proc and load from cache for rl mapping
* fix: refactor sft and rl trainer to set same base args
* feat: add report_to to set run name
* fix: consolidate handling of fp16, bf16, tf32 kwarg
* chore: consolidate eval_strat, loraplus, lr sched, max_length
* fix: deprecate old types
* fix: adding missing Any
* fix: max_steps incorrectly set
* fix: remove unnecessary datacollator kwarg insert and pop
* fix: update default max_steps
* fix: add missing weight_decay handling
* fix: ignore max_length for grpo
* feat: update CI on trainer_builder
* fix: comments
* improve handling of warmup/logging steps
* use transformers default for logging steps, not None
* fix: remove redundant override
* fix: lint
* feat: allow custom optim for rl methods
* fix: duplicate optim setting
* fix(test): set sequence_parallel_degree default in base cfg
* feat: add handling for seed and SP/ring-attn config
* chore: add back return typing from rebase
* fix(test): use RLType directly to skip needing to validate
* feat: split training builder into sub modules
* fix: remove deprecated clause
* chore: add missing config to doc
* fix: update quarto autodoc
* fix: import path for trainer builder and submodules
* fix: remove redundant configs from rebase mistake
* chore: simplify dynamo check
* fix: optimizer_cls_and_kwargs to be passed into trainer_kwargs
* fix: add missing rex from rebase
* fix: move pop optimizer_cls_and_kwargs
* fix: pop optimizer cls in rl too
* fix: leftover bug from rebase
* fix: update handling of trainer_cls in RL
* fix: address pr feedback
* feat: call hook_pre_create_trainer for rl
* chore: lint
* fix: return notimplemented for ppo
* feat: moved torch compile to base and refactor collator setting
* chore: remove unused importlib.util import
* fix: optimizer cls not being popped
* feat: move epoch setting to base
* fix: catch unhandled custom optimizer
* fix: remove duplicate lora plus setting
* chore: refactor if condition
* chore: refactor set_base_training_args into smaller modules
* fix: address TrainerBuilderBase class variables to instance var
* fix: add handling for beta3 and episilon2
* fix: change to pass dict via arg instead of updating dict
* chore: simplify if condition
* fix: force access to lr & weight decay in case not provided to early error
* fix: remove log sweep
* chore: refactor if condition
* fix: address renamed cfg
* fix: improve handling of cosine hyp
* fix: remove unused params
* chore: refactor
* chore: clarify doc safetensors
* fix: update import path to be unified following comments
* fix: duplicate kwargs passed
* feat: return separate trainer_kwargs
* chore: refactor
* chore: refactor based on comments
* chore: refactor based on comments
* fix: move gpustats callback to base
* chore: create trainer_cls_args first based on comments
* fix: ipo label smoothing passed incorrectly
* feat: add optimizer parity for RL methods with test
* feat: add parity for optimizer in RM/PRM and add test
* fix: remove redundant function override for orpo/cpo batch metrics
* fix: improve handling of dpo_label_smoothing and merge issue
* fix: test fixture returning wrong field
* fix: address avoid direct modify fixture
* chore: minor refactor
* Revert "chore: refactor"
This reverts commit 99c8859eb0.
* feat: rename trainer_builder to builders
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* offload activations to disk instead of CPU RAM
* add prefetch
* Disco :dance:
* include offload_disk in e2e test for AC
* document and make sure to cleanup
* fix annotation to match docs
* fix docs build
* 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>
* guard return if ring attn alrady registered
* add docs link, bits in multi-gpu docs, remove save model callback (subsumed by HF trainers)
* configurable heads_k_stride from ring-flash-attn hf adapter
* current
not clean working version
move torch trainer to do_cli
update code with config changes and clean up
edit config
cleanup
add run name to trainer
* address comments
* use axolotl train in multigpu tests and add ray tests for multi-gpu
* accelerate uses underscores for main_process_port arg
* chore: lint
* fix order of accelerate args
* include ray train in docker images
* current
not clean working version
move torch trainer to do_cli
update code with config changes and clean up
edit config
cleanup
add run name to trainer
* address comments
* use axolotl train in multigpu tests and add ray tests for multi-gpu
* accelerate uses underscores for main_process_port arg
* chore: lint
* fix order of accelerate args
* include ray train in docker images
* fix bf16 resolution behavior
* move dtype logic
* x
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* rename
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* add to sidebar
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* Apply suggestions from code review
Co-authored-by: Eric Tang <46737979+erictang000@users.noreply.github.com>
* Update docs/ray-integration.qmd
Co-authored-by: Eric Tang <46737979+erictang000@users.noreply.github.com>
* pre-commit fixes
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
* use output_dir instead of hardcoded saves path
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* bugfix storage dir
* change type\ for resources_per_worker
---------
Signed-off-by: SumanthRH <sumanthrh@anyscale.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: SumanthRH <sumanthrh@anyscale.com>
Co-authored-by: Sumanth R Hegde <39546518+SumanthRH@users.noreply.github.com>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* Add unsloth rope embeddings support
* support for models weights in 4bit and do some memory gc
* use accelerate logger
* add unsloth llama rms norm optims
* update docs for unsloth
* more docs info
