chore(config): refactor old mistral config (#1435)

Train parameters exclusively in specific ranges (#1390)

FDSP + QLoRA (#1378)

Mps mistral lora (#1292) [skip ci]

fix(examples): remove is_*_derived as it's parsed automatically (#1297)

Add seq2seq eval benchmark callback (#1274)

Mixtral fixes 20240124 (#1192) [skip ci]

Fine-Tuning Mistral-7b for Real-World Chatbot Applications Using Axolotl (Lora used) (#1155)

set fp16 to false if bf16, update bf16: auto in example YAMLs (#1122) [skip ci]

Set eval_sample_packing to false in mistral config.yaml (#1003)

set output_router_logits for mixtral config: (#995)

change val size (#992)

Fix Deepspeed loading (#950)

new evals_per_epoch and saves_per_epoch to make things cleaner (#944)

Mixtral official (#942)

update to latest transformers for mixstral support (#929)

Mixtral multipack (#928)

Feat(wandb): Refactor to be more flexible (#767)

feature: loss watchdog for terminating training runs that are failing (#899)

don't compile deepspeed or bitsandbytes from source (#837)

fix eval_steps to be a sane default (#797)

disable eval table w sample packing in examples (#778)

simplify by removing duplicate base_model_config (#772)

Fix: lowercase `True` values in config (#713)

Get qlora mistral-7b fine tuning working on a single 4090 (#708)

fix unneeded space (#699)

lint

new lr, sample pack

Fix: Higher vram usage for mistral and sample_packing (#691)

Adding qlora config for Mistral (#675)

prepared dataset caching, other misc fixes (#665)

Update mistral/README.md (#647)

Feat: Add example for Mistral (#644)