* mixtral multipack
* use mixtral model
* sample yml
* calculate cu_seqlens properly
* use updated flash ettention setting
* attn var checks
* force use of flash attention 2 for packing
* lint
* disable future fix for now
* update support table
* support for mamba
* more mamba fixes
* use fork for mamba kwargs fix
* grad checkpointing doesn't work
* fix extras for mamaba
* mamba loss fix
* use fp32 and remove verbose logging
* mamba fixes
* fix collator for mamba
* set model_type on training_args
* don't save safetensors for mamba
* update mamba config to disable safetensor checkpooints, install for tests
* no evals for mamba tests
* handle save_pretrained
* handle unused safetensors arg
* Feat: Update to handle wandb env better
* chore: rename wandb_run_id to wandb_name
* feat: add new recommendation and update config
* fix: indent and pop disabled env if project passed
* feat: test env set for wandb and recommendation
* feat: update to use wandb_name and allow id
* chore: add info to readme
* add phi modeling from hf
* update for packing and use new modeling class for phi
* update e2e tests for phi to use new model name
* update example phi to also use new phi model name
* use AutoModelForCausalLM for phi lora since sample packing isn't supported
* various bugfixes
use latest tinyllama release
check if val_set_size is empty first
update sdp and xformers llama patches for updated upstream transformers
fix system prompt when no input
calculate total and total supervised tokens even when not sample packing
* add fix for when eval size is estimated to be too small
* should be len 1 for dataset length
* add catchall kwargs
* Adding qlora config for Mistral
Contains fix for Mistral FA issue - ValueError: You are attempting to perform batched generation with padding_side='right' this may lead to unexpected behaviour for Flash Attention version of Mistral. Make sure to call tokenizer.padding_side = 'left' before tokenizing the input.
Fix for now is to set sample_packing: true and pad_to_sequence_len: true
* Renamed to qlora.yml
* Feat: Add support for upstream FA2
* chore: add is_falcon_derived_model: true to examples
* chore: add config to readme for documentation
* feat: add extra model types
* fix: remove old falcon flash patch
* chore: pin transformers and accelerate
* more sane defaults for openllama 3b used for quickstarts
* don't use bf16 for quickstart to simplify gpu compatibility
* use the update openlm-research/open_llama_3b_v2 models
* phi sequence packing
* sample packing fixes
* fix linting
* fix inference and phi e2e tests
* update phi example now that sample packing works
* wandb import keeps getting moved around
* auto gptq support
* more tweaks and add yml
* remove old gptq docker
* don't need explicit peft install for tests
* fix setup.py to use extra index url
install torch for tests
fix cuda version for autogptq index
set torch in requirements so that it installs properly
move gptq install around to work with github cicd
* gptq doesn't play well with sample packing
* address pr feedback
* remove torch install for now
* set quantization_config from model config
* Fix the implementation for getting quant config from model config
