* upgrade liger to 0.3.1
* update docs and example
* skip duplicate code check
* Update src/axolotl/integrations/liger/args.py
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* Update README.md
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* add logging
* chore: lint
* add test case
* upgrade liger and transformers
* also upgrade accelerate
* use kwargs to support patch release
* make sure prepared path is empty for test
* use transfromers 4.46.1 since 4.46.2 breaks fsdp
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* Allow using tokenizer's default chat template with fallbacks
Summary of changes:
1. Adds `tokenizer_default` as option for `chat_template` in
`chat_template` prompt strategy that allows using the chat template
from tokenizer's config.json
2. Allows falling back to chat templates available in axolotl if
tokenizer does not have a chat template
3. Adds a mistral chat template which supports system message - taken
from https://github.com/chujiezheng/chat_templates/blob/main/chat_templates/mistral-instruct.jinja
---
Why?
Many popular models are not trained with chatml format. As a result for
the model to correctly learn chatml we have to turn on train_on_inputs
which requires more compute and time. If we can use the model's already
learned chat template we can just learn the output tokens
---
Todo:
- Write tests
* Add tests
* Fix lint and bug post merge from main
* Add option `chat_template_jinja` to provide a jinja template
* remove custom mistral template
* Address review comments and add docs
* Update docs/dataset-formats/conversation.qmd
Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
* fix: set default to tokenizer template
* Merge branch 'main' into cj_tokenizer_default_prompt_template
* chore: remove redundant function
* fix: re-arrange enum declaration position
* fix: refactor artifact left from main merge
* feat(doc): updated config with chat template options and clarified examples
* chore: clarify doc
* chore: added example for non-default template
* chore: refactor
* fix: test
* fix: config being dropped and unittest to catch that
* chore: lint
* chore: skip duplicate
* fix: rename var after merge
* feat: add test for levy's dpo case
* fix: remove default setting on edge case where chat template overriden in dataset section
* feat: handle sharegpt deprecation better in docs
* feat: add example using fallback
* feat: handles chat_template requiring specific user/assistant order
* fix: update test based on new defaults
* fix: imported name incorrectly updated on merge
* chore: lint
* fix: update dummy message to prevent potential overlap with real content
* fix(doc): formatting
* fix: update bradleyterry to use new chat_template
---------
Co-authored-by: Chirag Jain <jain.chirag925@gmail.com>
* Add first version of a Comet integration
* Remove debug prints
* Add test for Comet Configuration transformation to env variables
* Fix last lint warning
* Update Readme for Comet logging documentation
* Update Comet integration to be optional, update code and tests
* Add documentation for Comet configuration
* Add missing check
* 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
* 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
---------
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
