* make mlflow optional
* fix xformers
don't patch swiglu if xformers not working
fix the check for xformers swiglu
* fix install of xformers with extra index url for docker builds
* fix docker build arg quoting
* wip modal for ci
* handle falcon layernorms better
* update
* rebuild the template each time with the pseudo-ARGS
* fix ref
* update tests to use modal
* cleanup ci script
* make sure to install jinja2 also
* kickoff the gh action on gh hosted runners and specify num gpus
* add a basic notebook for lab users in the root
* update notebook and fix cors for jupyter
* cell is code
* fix eval batch size check
* remove intro notebook
* attempt to also run e2e tests that needs gpus
* fix stray quote
* checkout specific github ref
* dockerfile for tests with proper checkout
ensure wandb is dissabled for docker pytests
clear wandb env after testing
clear wandb env after testing
make sure to provide a default val for pop
tryin skipping wandb validation tests
explicitly disable wandb in the e2e tests
explicitly report_to None to see if that fixes the docker e2e tests
split gpu from non-gpu unit tests
skip bf16 check in test for now
build docker w/o cache since it uses branch name ref
revert some changes now that caching is fixed
skip bf16 check if on gpu w support
* pytest skip for auto-gptq requirements
* skip mamba tests for now, split multipack and non packed lora llama tests
* split tests that use monkeypatches
* fix relative import for prev commit
* move other tests using monkeypatches to the correct run
* add torch to requirements.txt at build time to force version to stick
* fix xformers check
* better handling of xformers based on installed torch version
* fix for ci w/o torch
* 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
* update readme to point to direct link to runpod template, cleanup install instrucitons
* default install flash-attn and auto-gptq now too
* update readme w flash-attn extra
* fix version in setup
* 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
* flash attn pip
* add packaging
* add packaging to apt get
* install flash attn in dockerfile
* remove unused whls
* add wheel
* clean up pr
fix packaging requirement for ci
upgrade pip for ci
skip build isolation for requiremnents to get flash-attn working
install flash-attn seperately
* install wheel for ci
* no flash-attn for basic cicd
* install flash-attn as pip extras
---------
Co-authored-by: Ubuntu <mgh@mgh-vm.wsyvwcia0jxedeyrchqg425tpb.ax.internal.cloudapp.net>
Co-authored-by: mhenrichsen <some_email@hey.com>
Co-authored-by: Mads Henrichsen <mads@BrbartiendeMads.lan>
Co-authored-by: Wing Lian <wing.lian@gmail.com>
* drop cuda117/torch 1.13.1 from support, pin flash attention to v2.0.1, rm torchvision/torchaudio install
* gptq base build not needed. add sm 9.0 support
