* don't set peft_config on grpo to prevent double peft wrap
* remove overrides needed to support bug
* fix grpo tests
* require more CPU for multigpu to help with torch compile for vllm
* make setting `adam_beta3` and `adam_epsilon2` work correctly
* update config docs so users know args are specific to CAME optim
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Co-authored-by: Wing Lian <wing@axolotl.ai>
* offload activations to disk instead of CPU RAM
* add prefetch
* Disco :dance:
* include offload_disk in e2e test for AC
* document and make sure to cleanup
* fix annotation to match docs
* fix docs build
* address PR feedback
* update doc and skip brittle grpo test
* fix the path to run the multigpu tests
* increase timeout, use LOC instead of NVL
* typo
* use hf cache from s3 backed cloudfront
* mark grpo as flaky test dues to vllm start
* lean mistral ft tests, remove e2e torch 2.4.1 test
* make sure to pass save_only_model for RL
* more tests to make ci leaner, add cleanup to modal ci
* fix module for import in e2e tests
* use mp spawn to prevent deadlocks with packing
* make sure cleanup shell script is executable when cloned out
* fsdp embeddings should be float32 per comment
* patch peft to not upcast everything
* add tabs back to code check
* fix import
* add configurable option and fix check
* add check for dtypes
* move embeddings test to patch dir
* fix test
* fix comment and logic
* improve readability of multipack sampler
* parallel bin packing
fix error with lambda and pickling
make sure things are in float instead of np.float
* annotations and comments update
* support for configurable group and bin size for sample packing
* fix missing map back to original indices
* feat(doc): add split_thinking docs
* fix: link config.qmd to conversation.qmd for split_thinking example
* update thinking => reasoning_content in messages format
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* repop cache
* pre-cache as a step
* fix the name
* add reason for pytest skipif
* restore pytorch matrix
* remove max-parallel now that we've optimized this a bit
* Adds example for training a TTS model on top of a LLM.
* Update examples/orpheus/finetune.yml
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* Update examples/orpheus/finetune.yml
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* Update README.md to clarify GPU requirements for finetuning Orpheus TTS model
* Update finetune.yml to use the new base model canopylabs/orpheus-3b-0.1-pretrained
* Update finetune.yml and README.md for consistency and clarity
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* only configure logging on cli to play nicely with colab
* allow reloading the config on the fly from a dict
* make sure to use dict for yaml
* reuse existing function for load
* make cli args optional
* mps fix and respect max_steps
