* 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
* kd fixes
* fix collator setup
* fix input args
* better handling to drop string fields for kd with raw dataset
* kd trainer has kd temp as part of the init
* drop top_k before softmax
* simplfy and remove zscore
* WIP chunked KD loss with autograd wrapper
* more fixes and liger-type chunked loss
* collator cls for plugins
* remove debugging
* additional plugin collator kwargs, don't scale up kd loss by t^2
* don't need temp arg to distill method
* online kd wip
* add close to comment block
* suport sampling params/max new tokens
* handle when no custom collator is used in plugins
* logsumexp trick:
* fix check
* shift off the first empty token
* fix length of padding
* use max not min
* temp scale kd loss at end
* support for dynamic plugin training args mixins and symmetric kl
* chore: lint
* fix trainer callback base class
* Fix decay
* accept compressed responses for smaller wire payload
* post-rebase lint
* more KD updates
* increase hyperparams_count for gradients for added normalize_topk
* fix to remove attention_mask
* rename vars for consistency
* fix rebase issues
* default to dropping last batch in multipack batch sampler
* improve handling of train len
* init collator_cls_and_kwargs
* explicit drop_last=False when checking for multipack completeness
* use separate v2 loader for kd
* fix kd tests to use subprocess so it picks up kd training args
* default value for kd_beta arg
* use updated dataset for ci
* longer timeout for e2e
* add uv tooling for e2e gpu tests
* fixes from PR feedback
* simplify check
* fix env var
* make sure to use uv for other install
* use raw_dockerfile_image
* Fix import
* fix args to experimental dockerfile image call
* use updated modal versions
* bump hf deps
* upgrade liger-kernel too
* install cce from fork for transformers fix
* fix reference to vocab size in gemma3 patch
* use padding_idx instead of pad_token_id
* remove fixed gemma3 patch
* use updated cce fork
* fix local mllama cce patches w docstring
* add test for multipack with trainer setup and fix trainer for trainer refactor upstream
* bump modal version
* guard for iterable datasetS
* mllama model arch layout changed in latest transformers
* fix batch sampler with drop_last
* fix: address upstream vlm changes for lora
* fix: update references to old lora target path
* fix: remove mllama fa2 patch due to upstream fix
* fix: lora kernel patch path for multimodal models
* fix: removed mllama from quarto
* run test for came optim on 2.6.0+
* fix fsdp2 patch and remove deprecated patch
* make sure to set sequence_parallel_degree for grpo
* Add SP test for GRPO
* add sp to grpo config for trainer
* use reward_funcs as kwarg to grpo trainer
* fix the comprehension for reward funcs
* reward funcs already passed in as args
* init sp_group right before training
* fix check for adding models to SP context
* make sure to pass args to super
* upgrade deepspeed
* use updated trl and add reasoning flags for vllm
* patch the worker
---------
Co-authored-by: NanoCode012 <nano@axolotl.ai>
* 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
* 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
* Add: SFTPlugin with llmcompressor
* Update: review comments!
* Add:llmcompressor instalable
* pre commit hooks
* Use: warning over warn
* Revert: TODO's
* Update llmcompressor version to latest
* Apply suggestions from @markurtz
Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com>
* Address review comments from @markurtz
* Add: llcompressor installable
* Rename: sft.yaml to sparse-finetuning.yaml
* Use: absolute import
* Update model config
* Move: LLMCompressorPlugin into it's own submodule
* Add: `llm_compressor` integration documentation
* Rebase and updates!
* Tests, Style, Updates
* Add: .qmd file
* Address Review Comments:
* deleted redundant docs/llm_compressor.qmd
* incorporated feedback in integration README.md
* added llmcompressor integration to docs/custom_integrations.qmd
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Add: line about further optimizations using llmcompressor
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Apply patch from @winglian
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* Fix: Test
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* additional fixes for docker and saving compressed
* split llmcompressor from vllm checks
* Reset session between tests
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
* move decorator to test method instead of class
* make sure to reset the session after each test
* move import of llmcompressor to reset session inside test
---------
Signed-off-by: Rahul Tuli <rtuli@redhat.com>
Co-authored-by: Mark Kurtz <mark.j.kurtz@gmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
* update trl to 0.17.0
* grpo + vllm no longer supported with 2.5.1 due to vllm constraints
* disable VLLM_USE_V1 for ci
* imporve handle killing off of multiprocessing vllm service
* debug why this doesn't run in CI
* increase vllm wait time
* increase timeout to 5min
* upgrade to vllm 0.8.4
* dump out the vllm log for debugging
* use debug logging
* increase vllm start timeout
* use NVL instead
* disable torch compile cache
* revert some commented checks now that grpo tests are fixed
* increase vllm timeoout back to 5min
* builds for torch==2.7.0
* use xformers==0.0.29.post3
* no vllm support with torch 2.7
* update default, fix conditional
* no xformers for 270
* no vllm on 2.7.0 for multigpu test too
* remove deprecated verbose arg from scheduler
* 2.7.0 tests on cpu
* llama4 support
* add xet support [skip ci]
* be flexible on transformers version and skip test on version
* don't use deepspeed for the fix_untrained_tokens test
* reordering to trigger torch 2.6.0 tests first
* slightly smaller train set
* use 4.51.0 for now
* remove stray print, add llama4 chat template to schema, bump peft to 0.15.1
* patches to make llama4 performant
* add preliminary fp8 support
