* 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
* Add a config not to shuffle merged dataset
* Update README.md
* Update src/axolotl/utils/config/models/input/v0_4_1/__init__.py
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* invert the condition name
* update README
* info -> debug
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* orpo trainer
* rl handling for orpo
* support for remove_unused_columns
* orpo fixes
* fix loader for orpo
* chore: lint
* fix default for remove_unused_columns
* roll ORPO into the main AxolotlTrainer so it can be compatible with some of the other techniques like relora
* better handling of system message for orpo
* revert system prompt changes for chat templtes
* no need for else condition
* split dataset parsing into it's own component
* Add Glaive conversation format support
* fix black formatting errors
* Fix black and pylint formatting errors
* only set role_key_tool if provided in the dataset constructor
* Update src/axolotl/prompt_strategies/sharegpt.py
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* sharegpt test
* tokenizer test
* fix formatting
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* wip qlora + fsdp fixes
* more fixes
* make sure to load the lora 🤦
* only setup quantized meta on non-zero rank:
* only run setup_quantized_peft_meta_for_training for qlora+fsdp
* more fixes for qlora+fsdp
* chore: lint
* add example yml
* support mistral too
* fix for model_type and add mixtral support too
* set cpu_offload: false to reduce vram, constrain new accleerator logic to qlora + fsdp
* refactor for duplicate code
* plain input/output prompt strategy w/o chat templates
* disable duplicate code check
* make sure to add an eos/eot token to the end of the output so it will stop
* multi turn segement support and test
* add missing evals_per_epoch setting
* more pydantic fixes
* more fixes
* move test from normalization to validation
* increase eval size for sample packing tests
* support user-defined prompt processing strategies for dpo
* interpret dict dataset types as user-defined
* fix lint errors
* setup pydantic config for validation of User defined DPO
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* WIP conversion to use pydantic for config validation
* wip, more fields, add capabilities
* wip
* update pydantic validation to match existing tests
* tweak requirements
* setup deprecated paams pydantic model
* more validations
* wrap up rest of the validations
* flesh out the rest of the options from the readme into pydantic
* fix model validators as class methods
remember to return in validator
missing return
add missing relora attributes
fix test for DictDefault change
fix sys template for mistral from fastchat change in PR 2872
fix test for batch size warning
* more missing attributes for cfg
* updates from PR feedback
* fix validation for datasets and pretrain datasets
* fix test for lora check
* 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
* Allow load_best_model_at_end when using test_datasets and val_set_size is zero for custom evaluation datasets
* Fixed formatting following failed Lint check
