0.8.1 version

src/axolotl/__init__.py

@@ -4,4 +4,4 @@ import pkgutil
 
 __path__ = pkgutil.extend_path(__path__, __name__)  # Make this a namespace package
 
-__version__ = "0.8.0"
+__version__ = "0.8.1"

src/axolotl/integrations/cut_cross_entropy/monkeypatch/llama4.py

@@ -26,7 +26,6 @@ from transformers.utils import (
 )
 
 _PATCH_OPTS: PatchOptions | None = None
-RESET_LM_HEAD = True
 
 
 @add_start_docstrings_to_model_forward(LLAMA4_INPUTS_DOCSTRING)
@@ -309,16 +308,7 @@ def cce_forward_multimodal(
 
     if _PATCH_OPTS is not None and _PATCH_OPTS.use_lce(labels, self.training):
         assert labels is not None
-
+        # TODO: check if need to handle attention_mask
-        # reset lm head gradient on first pass.
-        # linear model has some lm_head weight issue
-        # see https://github.com/axolotl-ai-cloud/axolotl/pull/2505
-        global RESET_LM_HEAD  # pylint: disable=global-statement
-        if RESET_LM_HEAD:
-            RESET_LM_HEAD = False
-            self.language_model.lm_head.weight.requires_grad_(False)  # Detach
-            self.language_model.lm_head.weight.requires_grad_(True)  # Reattach
-
         loss = apply_lce(
             hidden_states,
             self.language_model.lm_head.weight,
@@ -383,7 +373,11 @@ def patch_llama4_text(
 
         return maybe_model
 
-    modeling_llama4.Llama4ForCausalLM.forward = cce_forward
+    setattr(
+        modeling_llama4.Llama4ForCausalLM,
+        "forward",
+        cce_forward,
+    )
     return None
 
 
@@ -409,8 +403,12 @@ def patch_llama4(
         )
         return maybe_model
 
-    modeling_llama4.Llama4ForConditionalGeneration.forward = cce_forward_multimodal
+    setattr(
+        modeling_llama4.Llama4ForConditionalGeneration,
+        "forward",
+        cce_forward_multimodal,
+    )
 
     # patch the causal language model
-    modeling_llama4.Llama4ForCausalLM.forward = cce_forward
+    setattr(modeling_llama4.Llama4ForCausalLM, "forward", cce_forward)
     return None