* Correctly handle splits for datasets.arrow_dataset.Dataset objects
The `load_tokenized_prepared_datasets` function currently has logic for loading a dataset from local path that always checks if a split is in the dataset. The problem is, if the dataset is loaded using `load_from_disk` and it is an Arrow-based dataset, *there is no* split information. Instead what happens is, by calling `split in ds`, it presumably searches through all the rows and columns of the arrow dataset object to find e.g., 'train' assuming `split == 'train'`. This causes the program to hang.
See https://chat.openai.com/share/0d567dbd-d60b-4079-9040-e1de58a4dff3 for context.
* chore: lint
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Co-authored-by: Wing Lian <wing.lian@gmail.com>
* can configure name of split of pretraining dataset
* streaming data and dataset map
* text column customized
* allow text_column to be set in pretrain
* pretrain type
* load a bit of the dataset
* fix dataset where splits have separate configs
* ok name param here is the config
* whitespace
* add lisa support
* fix default and fix attribute traversal for layers
* improve lisa callback logging
* fix LISA by ensuring params are not frozen during __init__
* example config for lisa
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Co-authored-by: Aman Karmani <aman@tmm1.net>
* 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
