Fix: quantize and target moe layers in transformers v5 for adapters and many misc fixes (#3439)

* fix: saving clones state dict

* fix: apply fix for only CP mode

* fix: add dropout check when using lora target param

* fix: re-add patch from transformers PR #39866

* feat: add moe quant to test by ved

* fix: try match target param properly end with

* fix: clear cache per param quant

* fix: attempt on-load quantize experts instead of post-load

* fix: attempt disable async load

* chore: add log

* chore: adjust log

* fix: remove cuda alloc for moe and enable async load

* chore: remove leftover logs

* chore: add extra empty cache

* fix(doc): clarify support

* fix: handle fsdp2 for paramwrapper dtensor

* feat: attempt to quant experts in 8bit mode too

* feat: attempt to release bf16 experts from vram

* feat: upgrade cce

* fix: fsdp2 init_sharded_param load int8/uint4 dtensor as
require_grad=true on init

* fix: remove unnecessary gc and empty cache

* Revert "fix: remove unnecessary gc and empty cache"

This reverts commit 1d54518990.

* fix: do not call full_tensor on non-dtensors

* fix: attempt to address fsdp2 with quant exp high loss

* fix: attempt lora quant experts wrong dim

* fix: ensure require_grad patch applied for lora 8bit

* fix: attempt lora 8bit fsdp2

* fix: attribute access on save for lora 8bit fsdp2

* fix: wrong weight attrib access

* chore(refactor): add config, re-arrange position of patches, clean
comments

* feat: add example docs

* chore: cherry pick trinity fixes from PR 3399

* chore: comments refactor; add guards

* fix: guard using wrong key

* fix: mamba save does not accept main process param

* fix: guard prevent double hook

* fix: move gc to upper scope

* chore: add comment on proxy forward patch

* fix: add comment to clarify

* feat: add test idempotency

* fix: AttributeError: `e_score_correction_bias` is not an nn.Parameter

* fix: AttributeError: 'NoneType' object has no attribute 'to'

* fix: update docs on cpu_ram_efficient_loading

scripts/cutcrossentropy_install.py

@@ -29,5 +29,5 @@ UV_PREFIX = "uv " if USE_UV else ""
 
 print(
     UNINSTALL_PREFIX
-    + f'{UV_PREFIX}pip install "cut-cross-entropy[transformers] @ git+https://github.com/axolotl-ai-cloud/ml-cross-entropy.git@58d6572"'
+    + f'{UV_PREFIX}pip install "cut-cross-entropy[transformers] @ git+https://github.com/axolotl-ai-cloud/ml-cross-entropy.git@a668583"'
 )