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.ipynb_checkpoints/modeling_mic21-checkpoint.py

@@ -41,7 +41,7 @@ class MIC21SummarizerModel(PreTrainedModel):
         self.projection_layer = torch.nn.Linear(49, self.components["llm"].config.hidden_size, dtype=torch.float)
         
         #self.projection_norm = torch.nn.LayerNorm(49, eps=1e-5, bias=True, device=f"cuda:{self.in_device}")
-        self.projection_layer = torch.nn.Linear(49, self.components["llm"].config.hidden_size, dtype=torch.float)
+        self.projection_norm = torch.nn.LayerNorm(49, eps=1e-5, bias=True)
         self.projection_dropout = torch.nn.Dropout(0.1)
 
         for param in self.components["image_model"].parameters():

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cc567081fc6c05d3793d6f0fa3f6c5be74bc8719905b685a8abe08575eb0bfb3
-size 409808
+oid sha256:3c68b292e8a97ff24c70317c8623e496d3b51cdaddb682790fc5c8435f1f3459
+size 410368

modeling_mic21.py

@@ -41,7 +41,7 @@ class MIC21SummarizerModel(PreTrainedModel):
         self.projection_layer = torch.nn.Linear(49, self.components["llm"].config.hidden_size, dtype=torch.float)
         
         #self.projection_norm = torch.nn.LayerNorm(49, eps=1e-5, bias=True, device=f"cuda:{self.in_device}")
-        self.projection_layer = torch.nn.Linear(49, self.components["llm"].config.hidden_size, dtype=torch.float)
+        self.projection_norm = torch.nn.LayerNorm(49, eps=1e-5, bias=True)
         self.projection_dropout = torch.nn.Dropout(0.1)
 
         for param in self.components["image_model"].parameters():