Update mistral/README.md (#647)

Feat: Add example for Mistral (#644)

Fix(cfg): Add validation for save_strategy and eval_strategy (#633)

Mistral flash attn packing (#646)

Warn users to login to HuggingFace (#645)

Fix bug in dataset loading (#284)

Correct typos in datasets.py (#639)

skip some flash attn patches unless explicitly enabled (#643)

use fastchat conversations template (#578)

update for recent transformers updates (#636)

attention_mask not needed for training (#642)

eval_table isn't quite stable enough to be in default llama configs (#637)

Feat: Add support for upstream FA2 (#626)

Added quotes to the pip install -e command to fix an incompatibility with shells that do glob expansion like zsh (#632)

Merge pull request #629 from OpenAccess-AI-Collective/chore/-change-default-model

Fix: Fail bf16 check when running on cpu during merge (#631)

default model changed

Feat(doc): Add eval_sample_packing to doc (#625)

tweak: improve base builder for smaller layers (#500)

better handling and logging of empty sharegpt turns (#603)

create a model card with axolotl badge (#624)

update README w deepspeed info (#605)

chore(callback): Remove old peft saving code (#510)

misc fixes to add gptq tests (#621)

split completion text to sequence_len (#616)

run eval on the first step to get a baseline (#617)

let MAX_JOBS use the default since we're not resource constrained on our self-hosted runners (#427)

skip the gpu memory checks if the device is set to 'auto' (#609)

ignore wandb to resolve isort headaches (#619)

fix distributed devices (#612)

Create multi-node.md (#613)

Only run tests when a change to python files is made (#614)

Update requirements.txt (#610)

support to disable exllama for gptq (#604)

Delete duplicate lines (#606)

update dockerfile to not build evoformer since it fails the build (#607)

more sane defaults for openllama 3b used for quickstarts (#602)

improve handling for empty text on the tokenization step (#502)

Fix for check with cfg and merge_lora (#600)

minor tweaks to simplify (#597)

btlm and falcon monkey patches for flash attn (#566)

add bf16 check (#587)

Feat(data): Allow loading local csv and text (#594)

gather/broadcast the max value of the packing efficiency automatically (#463)

don't add position_ids for evals (#591)

optionally configure sample packing for evals (#589)

make phi training work with Loras (#588)

set fsdp state dict (#584)

pop block_cls since it's not an actual kwarg

don't resize embeddings if it's already large enough (#577)