Fix typos

src/adapters/models/__init__.py

@@ -20,6 +20,18 @@
 from .gptj.mixin_gptj import GPTJMLPAdaptersMixin, GPTJModelAdapterMixin
 from .llama.mixin_llama import LlamaForQuestionAnsweringAdapterMixin, LlamaModelAdapterMixin
 from .mistral.mixin_mistral import MistralModelAdapterMixin
+from .mllama.mixin_mllama import (
+    MllamaAdaptersMixin,
+    MllamaCrossAttentionDecoderLayerAdaptersMixin,
+    MllamaSelfAttentionDecoderLayerAdaptersMixin,
+    MllamaTextCrossAttentionAdaptersMixin,
+    MllamaTextModelAdaptersMixin,
+    MllamaTextSelfAttentionAdaptersMixin,
+    MllamaVisionAttentionAdaptersMixin,
+    MllamaVisionEncoderAdaptersMixin,
+    MllamaVisionEncoderLayerAdaptersMixin,
+    MllamaVisionModelAdaptersMixin,
+)
 from .plbart.mixin_plbart import (
     PLBartDecoderAdaptersMixin,
     PLBartDecoderWrapperAdaptersMixin,
@@ -42,17 +54,6 @@
 )
 from .xmod.mixin_xmod import XmodModelAdaptersMixin
 
-from .mllama.mixin_mllama import (
-    MllamaCrossAttentionDecoderLayerAdaptersMixin,
-    MllamaSelfAttentionDecoderLayerAdaptersMixin,
-    MllamaTextCrossAttentionAdaptersMixin,
-    MllamaTextModelAdaptersMixin,
-    MllamaTextSelfAttentionAdaptersMixin,
-    MllamaVisionAttentionAdaptersMixin,
-    MllamaVisionEncoderAdaptersMixin,
-    MllamaVisionEncoderLayerAdaptersMixin,
-    MllamaVisionModelAdaptersMixin,
-)
 
 # IMPORTANT: Only add classes to this mapping that are not copied into the adapters package
 MODEL_MIXIN_MAPPING = {
@@ -121,6 +122,7 @@
     "LlamaForQuestionAnswering": LlamaForQuestionAnsweringAdapterMixin,
     "MistralModel": MistralModelAdapterMixin,
     # Mulitmodal Llama
+    "MllamaModel": MllamaAdaptersMixin,
     "MllamaVisionModel": MllamaVisionModelAdaptersMixin,
     "MllamaTextModel": MllamaTextModelAdaptersMixin,
     "MllamaVisionEncoder": MllamaVisionEncoderAdaptersMixin,

src/adapters/models/auto/adapter_model.py

@@ -24,7 +24,7 @@
         ("llama", "LlamaAdapterModel"),
         ("mbart", "MBartAdapterModel"),
         ("mistral", "MistralAdapterModel"),
-        ("mllama", "MllamaAdapterModel")
+        ("mllama", "MllamaAdapterModel"),
         ("mt5", "MT5AdapterModel"),
         ("plbart", "PLBartAdapterModel"),
         ("roberta", "RobertaAdapterModel"),

src/adapters/models/mllama/mixin_mllama.py

@@ -5,6 +5,7 @@
 from ...methods.reft import ReftLayer, hook_fn
 from ...model_mixin import (
     EmbeddingAdaptersMixin,
+    EmbeddingAdaptersWrapperMixin,
     InvertibleAdaptersMixin,
     InvertibleAdaptersWrapperMixin,
     ModelBaseAdaptersMixin,
@@ -65,7 +66,7 @@ def init_adapters(self, model_config, adapters_config):
         super().init_adapters(model_config, adapters_config)
 
         # Register hook for post embedding forward
-        self.embeddings.register_forward_hook(self.post_embedding_forward)
+        self.embed_tokens.register_forward_hook(self.post_embedding_forward)
 
     def post_embedding_forward(self, module, args, embedding_output):
         embedding_output = self.invertible_adapters_forward(embedding_output)
@@ -77,23 +78,23 @@ def iter_layers(self) -> Iterable[Tuple[int, nn.Module]]:
             yield i, layer
 
 
-class MllamaAdaptersMixin(EmbeddingAdaptersMixin, InvertibleAdaptersWrapperMixin, ModelBaseAdaptersMixin):
+class MllamaAdaptersMixin(EmbeddingAdaptersWrapperMixin, InvertibleAdaptersWrapperMixin, ModelBaseAdaptersMixin):
     """
     Adds adapters to the MLLaMA model, handling both vision and text components.
     """
 
-    invertible_adapters_base_name = "language_model"  # Changed from text_model to match MLLaMA's naming
+    invertible_adapters_base_name = "language_model"
     support_prompt_tuning = False
 
     def iter_layers(self) -> Iterable[Tuple[int, nn.Module]]:
         layer_idx = 0
 
         # First iterate through vision model's local transformer layers
-        for _, layer in enumerate(self.vision_model.iter_layers()):
+        for _, layer in self.vision_model.iter_layers():
             yield layer_idx, layer
             layer_idx += 1
 
-        for _, layer in enumerate(self.language_model.layers):
+        for _, layer in self.language_model.iter_layers():
             yield layer_idx, layer
             layer_idx += 1