* upgrade peft to 0.16.0
* upgrade datasets to 4.0.0
* refactor dupes from merge/rebase
* fix check for fsdp1 + sharded_state_dict
* use full state dict for ci
* upgrade trl==0.19.1
* add vllm for tests for grpo
* fixes to work with latest trl
* need data_parallel_size config too
* support for vllm_mode for server / colocate
* vllm settings for colocate
* relax vllm version
* bump min hf hub for latest vllm support
* add hints on string literal for vllm mode
* use latest transformers 4.53.2
* tweak acceptable loss on flaky test_ds_zero3_packed test
* don't run flaky vllm/grpo tests for now
* FSDP2 args migration implementation
This commit implements the migration to FSDP2 arguments including:
- FSDP2 support with LoRA training
- DPO integration with FSDP2
- Model loading fixes and refactoring
- CPU offloading and PEFT handling
- Test updates and CI improvements
- Bug fixes for dtype errors and various edge cases
* tiled_mlp supports single gpu
* use checkpoint offloading for arctic training
* patch torch checkpoint too
* support for single gpu zero3
* add linkback to where it was copied from
* fix: do not add training and training_detail block by default
* fixed: magistral docs
* fix: address pad adding new fields and use built-in from_openai
* feat: try enable multiprocessing
* fix: check for keys before deleting attn_mask
* feat: add mistral pad test
* feat: add tool calling test
* feat: add devstral tokenizer tests
* fix: comma format
* chore: remove unused support_preprocessing as tokenizer is pickable now
* chore: update magistral doc
* feat: add devstral readme and example
* chore: refactor error handling
* densemixer plugin integration
* update readme with usage docs
* automatically find new integrations that aren't explicitly defined
* make sure to import os
* update transformers to 4.53.0
* remove attention_mask from signature columns if using packing
* remove attention_mask column from dataloader
* update signature of flash attn forward for ring attn patch
* fix FSDP
* patch ring-flash-attn with upstream signature fix
* fix patch indentation level
* fix the patch
* add batch flattening smoke test with loss check that works in older transformers
* fix patch
* don't drop attention mask for flex
* more fixes
* patch create_causal_mask for packing w flex
* global torch manual_seed fixture
* tweak loss checks
* fix patch and use single batch for flex
* don't need to reload
* fix causal mask patch
* use transformers patch releasE
* make sure env var is string
* make sure to drop attention mask for flex w packing for latest transformers patch release
* tweak loss
* guard on signature columns before removing attention mask
* bump loss
* set remove isn't chainable
* skip slow mistral test in 2.5.1
* fix: let users know to not call preprocess for vision mode
* fix: improve ux for pretraining dataset and skip prepare ds
* feat: add info to doc
* Update src/axolotl/cli/preprocess.py following comment
Co-authored-by: salman <salman.mohammadi@outlook.com>
---------
Co-authored-by: salman <salman.mohammadi@outlook.com>
* respect shuffle_merged_datasets for single dataset too
* update inline comment for behavior
Co-authored-by: NanoCode012 <nano@axolotl.ai>
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* feat: update handling for mistraltokenizer decode
* fix: update mistral common package version
* fix: to use correct release
* fix triton path
---------
Co-authored-by: Wing Lian <wing@axolotl.ai>
* ignore generation/endgeneration tags
Axolotl handles calculating the mask for assistant turns on its own, and as such these tags are not needed, however currently the analyzer does not recognize them at all and throws an error.
* feat: add phi4 tokenizer test and unblock gemma2
* fix: improve template
* chore: refactor
* chore: lint
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
Co-authored-by: Wing Lian <wing@axolotl.ai>
