diff --git a/models/demos/llama3/tests/multimodal/test_llama_cross_attention_transformer_text.py b/models/demos/llama3/tests/multimodal/test_llama_cross_attention_transformer_text.py
index 172531645c92..d72990b45b8e 100644
--- a/models/demos/llama3/tests/multimodal/test_llama_cross_attention_transformer_text.py
+++ b/models/demos/llama3/tests/multimodal/test_llama_cross_attention_transformer_text.py
@@ -58,7 +58,7 @@ def test_llama_cross_attention_transformer_text_inference(
     prefill_pcc_required = 0.98
     decode_pcc_required = 0.73
 
-    mesh_device.enable_async(True)
+    mesh_device.enable_async(False)
 
     model_args = TtModelArgs(mesh_device, max_batch_size=batch)
     # Limit the max seqlen to 4k to avoid OOM on host
diff --git a/models/demos/llama3/tt/model_config.py b/models/demos/llama3/tt/model_config.py
index 45fe46561c2e..a79c2649e5df 100644
--- a/models/demos/llama3/tt/model_config.py
+++ b/models/demos/llama3/tt/model_config.py
@@ -92,15 +92,15 @@ def __init__(self, mesh_device, instruct=False, dummy_weights=False, max_batch_s
             # Assert if all folders and files exist
             assert os.path.exists(
                 self.DEFAULT_CKPT_DIR
-            ), f"Checkpoint directory {self.DEFAULT_CKPT_DIR} does not exist, please use export LLAMA_CKPT_DIR=..."
+            ), f"Checkpoint directory {self.DEFAULT_CKPT_DIR} does not exist, please set LLAMA_DIR=... or LLAMA_CKPT_DIR=..."
             assert os.path.isfile(
                 self.DEFAULT_TOKENIZER_PATH + "/tokenizer.model"
-            ), f"Tokenizer file {self.DEFAULT_TOKENIZER_PATH + '/tokenizer.model'} does not exist, please use export LLAMA_TOKENIZER_PATH=..."
+            ), f"Tokenizer file {self.DEFAULT_TOKENIZER_PATH + '/tokenizer.model'} does not exist, please set LLAMA_TOKENIZER_PATH=..."
             if not os.path.exists(self.DEFAULT_CACHE_PATH):
                 os.makedirs(self.DEFAULT_CACHE_PATH)
             assert os.path.exists(
                 self.DEFAULT_CACHE_PATH
-            ), f"Cache directory {self.DEFAULT_CACHE_PATH} does not exist, please use export LLAMA_CACHE_PATH=..."
+            ), f"Cache directory {self.DEFAULT_CACHE_PATH} does not exist, please set LLAMA_CACHE_PATH=..."
             # Check if weights exist in the specified folder. If not warn the user to run the download and untar script.
         #            assert os.path.isfile(
         #                self.DEFAULT_CKPT_DIR + "/consolidated.00.pth"
diff --git a/models/demos/llama3/tt/multimodal/llama_cross_attention_transformer_text.py b/models/demos/llama3/tt/multimodal/llama_cross_attention_transformer_text.py
index 0c50b2128b0a..8abf0588cee4 100644
--- a/models/demos/llama3/tt/multimodal/llama_cross_attention_transformer_text.py
+++ b/models/demos/llama3/tt/multimodal/llama_cross_attention_transformer_text.py
@@ -2,20 +2,15 @@
 
 # SPDX-License-Identifier: Apache-2.0
 
-import os
 import math
 import ttnn
 import torch
-import torch.nn as nn
 from models.demos.llama3.tt.llama_decoder import TtTransformerBlock
 from models.demos.llama3.tt.multimodal.llama_cross_block import TtLlamaCrossAttentionTransformerBlock
-from models.demos.llama3.tt.llama_model import LMHead
 from models.demos.llama3.tt.distributed_norm import DistributedNorm
 from models.common.rmsnorm import RMSNorm
 import ttnn
-from typing import Optional
 from models.common.lightweightmodule import LightweightModule
-from models.demos.llama3.tt.llama_embedding import TtLlamaEmbedding
 
 from models.utility_functions import (
     nearest_32,
@@ -288,8 +283,9 @@ def forward(
 
         h = self.norm(h, mode=mode)
 
-        if mode == "decode":  # h is expected to be interleaved for the lm head
-            h = ttnn.sharded_to_interleaved(h)
+        # TODO: Switch to using dram-sharded LM haed and remove this
+        # Note: workaround for sharded_to_interleaved memory corruption (#15113)
+        h = ttnn.to_memory_config(h, ttnn.DRAM_MEMORY_CONFIG)
 
         seq_len = h.shape[2]
         MAX_MM_SEQ_LEN = 1024