* 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>
* upgrade to flash-attn 2.8.0.post2
* use cu126 with torch 2.6
* seems vllm 0.8.5.post1 not compatible with cuda12.6.3 and torch 2.6
* cu126 + torch 2.6 as the default
* use cu126 for multigpu w torch 2.6 too
* drop vllm for now from ci for now
