* fsdp embeddings should be float32 per comment
* patch peft to not upcast everything
* add tabs back to code check
* fix import
* add configurable option and fix check
* add check for dtypes
* move embeddings test to patch dir
* fix test
* fix comment and logic
* Add: SFTPlugin with llmcompressor
* Update: review comments!
* Add:llmcompressor instalable
* pre commit hooks
* Use: warning over warn
* Revert: TODO's
* Update llmcompressor version to latest
* Apply suggestions from @markurtz
Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com>
* Address review comments from @markurtz
* Add: llcompressor installable
* Rename: sft.yaml to sparse-finetuning.yaml
* Use: absolute import
* Update model config
* Move: LLMCompressorPlugin into it's own submodule
* Add: `llm_compressor` integration documentation
* Rebase and updates!
* Tests, Style, Updates
* Add: .qmd file
* Address Review Comments:
* deleted redundant docs/llm_compressor.qmd
* incorporated feedback in integration README.md
* added llmcompressor integration to docs/custom_integrations.qmd
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Add: line about further optimizations using llmcompressor
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Apply patch from @winglian
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Fix: Test
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* additional fixes for docker and saving compressed
* split llmcompressor from vllm checks
* Reset session between tests
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* move decorator to test method instead of class
* make sure to reset the session after each test
* move import of llmcompressor to reset session inside test
---------
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
* 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
* add e2e smoke test for using activation/gradient checkpointing with offload
* disable duplicate code check for the test
* fix relative import
* seq len too small to test this dataset with packing
* Fix checkpoint ptaching for tests
* make sure to validate the config before normalizing so defaults get set
* validation not needed for particular test
* remove duplicate validations
* set qlora correctly
* batch api HF adapter for ring-flash-attn; cleanup and improvements
* update
* adding all batch ring-flash-attn methods via single adapter
* removing pad_to_sequence_len=False for now
* fix
* updating docs to include batch SP
* review comments
* fixes for batch API funcs, simplify
* fixes
* fix
* updates
* add batch_zigzag smoke test
* 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>
* [ci] make e2e tests a bit faster by reducing test split size
* use 10% split of alpaca dataset to speed up dataset loading/tokenization
* reduce gas 4->2 for most e2e tests
* increase val set size for packing
* 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 gemma3 work with packing
* multi-gpu e2e for ci
* update gemma3 model namespace to use mirror
* add gradient checkpointing to multigpu e2e ci
* update gemma3 examples for use_reentrant and fix ddp find unused params
* fix tests for gemma3
* fix import for test utils
* set correct train loss for gemma3 e2e
* 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
* 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>
* 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
* 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
* feat: add config for optional parameters in a chat message
* chore: cleanup
* chore: fix nits and add light docs
* docs: update docs/dataset-formats/conversation.qmd
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* feat: configurable message mappings, jinja template analyzer
* chore: handle bradley terry
* docs: update docs
* refactor: change order of mappings, improve message transform
* refactor: make chat awware of property mappings
* chore: remove .python-version
* chore: revert change
* chore: add dataset validation to tests where appropriate
* chore: add dataset validation to tests where appropriate
* chore: clean up handling of ds_cfg
* chore: recursively serialize config
* make sure to use the return value from validate_config
* DefaultDict pickle/unpickle fix
* fix super call for override
* refactor: message fields
* chore: empty commit
* tests: validate config before using
* chore: add config validation to all e2e tests
* chore: add unneeded logging
* chore: add missed config validation
* chore: pass field_messages to prompter
* test: fix borked test
* chore: remove uninteded file
* chore: add deprecation warning and update chat_datasets script
* chore: lint
* refactor: message fields
* feat: update axolotlinputconfig and test_models
- add configdict import in axolotl/utils/config/models/input/v0_4_1/__init__.py
- remove unnecessary line breaks in sftdataset, dpodataset, ktodataset, stepwisesuperviseddataset classes
- update model_dump method in axolotlinputconfig to exclude none values
- correct typo in test_models.py comment
* feat: simplify dpodataset and ktodataset classes in config models
removed several optional fields from dpodataset and ktodataset classes in axolotl/utils/config/models/input/v0_4_1. this simplifies the configuration subsets for these datasets.
* feat: improve readability and structure in dataset configuration models
this commit enhances the readability and structure of the dataset configuration models in the `axolotl/utils/config/models/input/v0_4_1` module. it removes unused `configdict` import and adds line breaks to separate class definitions for better clarity. additionally, a minor documentation fix is included to ensure a newline at the end of the `stepwise_supervised.qmd` file.
* feat: change log level from info to debug in chattemplatestrategy
* feat(prompt_strategies): refactor chattemplateprompter and chattemplatestrategy
- Make `chat_template` a required parameter in `ChatTemplatePrompter` constructor
- Add default value for `message_property_mappings` in `ChatTemplatePrompter` constructor
- Add `messages_array_name` property to `ChatTemplatePrompter`
- Change `processor` type to Optional in `ChatTemplatePrompter`
- Add TypeError check for `processor` in `ChatTemplatePrompter.build_prompt`
- Remove `_messages` property from `ChatTemplateStrategy`
- Make `prompter` a required parameter and add type hint in `ChatTemplateStrategy` constructor
- Remove `messages` getter and setter from `ChatTemplateStrategy`
- Use `prompter.messages_array_name` in `ChatTemplateStrategy.get_conversation_thread`
- Remove condition to set `messages` field in `load` function
* feat(tests/utils): ignore type check in load_model call in test_models.py
* feat: improve type handling and test structure in chat templates
- Add return type hint for `get_chat_template` function in `chat_templates.py`
- Remove unnecessary assignment of `strategy.messages` in several test cases
- Add `messages_array_name` parameter to various test configurations in `test_chat_templates.py` and `test_chat_templates_advanced.py`
- Remove redundant `strategy.messages` assignment in `test_chat_templates_advanced.py`
* feat(axolotl): enhance chat strategy with datasetconfig support
This commit introduces support for DatasetConfig in the ChatTemplateStrategy. It also refines the strategy loader to handle different types of ds_cfg inputs and improves the clarity of the code by formatting and reordering. The key changes include:
- Importing Union from typing and BaseModel from pydantic.
- Adding DatasetConfig as an optional type for ds_cfg in StrategyLoader.
- Adjusting the handling of ds_cfg in StrategyLoader to account for BaseModel instances.
- Refactoring the prompter_params and strategy_params for better readability.
- Changing the reference from prompt[self.messages] to prompt[self.prompter.messages_array_name] in the is_prompt_batched method.
* feat: update message handling in btchattemplatestrategy
* Replace `self.messages` with direct string references to "chosen_messages" and "rejected_messages"
* Append system, user, and assistant content directly to "chosen_messages" and "rejected_messages"
* Add a new attribute "messages_array_name" to the `load` function parameters
* Remove the conditional attribute assignment for "field_messages" in the `load` function
* feat: add config validation in test_kd.py
- Import `validate_config` from `axolotl.utils.config`
- Validate the configuration in `test_llama_kd` and another function in `TestKnowledgeDistillation` class
* feat: enhance config validation and capabilities handling
* Import `EnvCapabilities` and `GPUCapabilities` from `axolotl.utils.config.models.internals`
* Update `validate_config` function to create `KTODataset` and `SFTDataset` instances using `dict(ds_cfg)`
* Replace `capabilities` and `env_capabilities` with instances of `GPUCapabilities` and `EnvCapabilities` respectively in `AxolotlConfigWCapabilities` model dump
* feat: update config validation in axolotl utils
- Remove import of `EnvCapabilities` and `GPUCapabilities` from `axolotl.utils.config.models.internals`
- Update `validate_config` function to use `capabilities` and `env_capabilities` directly instead of creating new instances of `GPUCapabilities` and `EnvCapabilities`
* feat: refactor strategyloader in chat_template.py
- Extracted the creation of strategy parameters into a separate function, `_get_strategy_params(cfg, dataset_config)`
- Created a new function, `_get_strategy_cls()`, to obtain the strategy class
- Replaced `ChatTemplateStrategy` with `strategy_cls` for strategy instantiation
* trigger CI
* chore: revert dataset config changes for kto/dpo
* subject: refactor: rename 'messages_array_name' to 'field_messages'
Body:
- Renamed 'messages_array_name' to 'field_messages' in 'ChatTemplatePrompter' class and its usages in 'chat_template.py'
- Updated 'load' function in 'bradley_terry/chat_template.py' to reflect the change
- Adjusted 'get_chat_template_msg_variables' and 'get_message_vars' methods in 'jinja_template_analyzer.py' to use the new variable name
- Modified 'StrategyLoader' in 'chat_template.py' to use 'field_messages'
- Updated tests in 'test_chat_templates.py' and 'test_chat_templates_advanced.py' to use 'field_messages' instead of 'messages_array_name'
* feat: refactor prompt strategies and update config models
* Remove redundant 'return None' in `axolotl/prompt_strategies/__init__.py`
* Simplify message handling in `axolotl/prompt_strategies/bradley_terry/chat_template.py` by using a single 'messages' list instead of separate 'chosen_messages' and 'rejected_messages' lists
* Update default 'message_property_mappings' in `axolotl/prompt_strategies/bradley_terry/chat_template.py`
* Add 'field_messages' field to `axolotl/utils/config/models/input/v0_4_1/__init__.py` configuration model
* chore: remove unused input
* chore: remove redundant type ignore
* fix: remove old configs and update examples
* fix: type check
* fix: remove loading old config in ChatMessage
* fix: update faq with potential new undefinederror
* fix: add debug if property mapped is not found
* chore: improve explanation for unmapped properties
* fix: update docs with new config
* chore: add note for deprecation config and del old config from dict
---------
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: NanoCode012 <nano@axolotl.ai>
