upgrade transformers==5.3.0 trl==0.29.0 kernels (#3459)

* upgrade transformers==5.3.0 trl==0.29.0 kernels

* use latest deepspeed fixes

* use corect image for cleanup

* fix test outputs for tokenizer fixes upstream

* fix import:

* keep trl at 0.28.0

* handle updated API

* use latest trl since 0.28.0 doesn't work with latest transformers

* use trl experimental for pad to length

* monkeypatch trl with ORPOTrainer so liger doesn't croak

* upgrade accelerate

* more fixes

* move patch for orpotrainer

* load the imports later

* remove use_logits_to_keep

* fix loss_type arg as a list

* fetch hf cache from s3

* just manually download the missing model for now

* lint for pre-commit update

* a few more missing models on disk

* fix: loss_type internally now list

* fix: remove deprecated code and raise deprecate

* fix: remove unneeded blocklist

* fix: remove reliance on transformers api to find package available

* chore: refactor shim for less sideeffect

* fix: silent trl experimental warning

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>

tests/test_tokenizers.py

@@ -84,7 +84,8 @@ class TestTokenizers:
             }
         )
         tokenizer = load_tokenizer(cfg)
-        assert tokenizer("<|im_start|>user")["input_ids"] == [1, 32000, 1404]
+        assert "LlamaTokenizer" in tokenizer.__class__.__name__
+        assert tokenizer("<|im_start|>user")["input_ids"] == [1, 32000, 1792]
         assert len(tokenizer) == 32001
 
         # ensure reloading the tokenizer again from cfg results in same vocab length