diff --git a/ludwig/models/llm.py b/ludwig/models/llm.py
index 52c67352fc6..217fd16e202 100644
--- a/ludwig/models/llm.py
+++ b/ludwig/models/llm.py
@@ -21,6 +21,7 @@
 from ludwig.utils.error_handling_utils import default_retry
 from ludwig.utils.llm_quantization_utils import convert_quantized_linear_to_linear
 from ludwig.utils.llm_utils import (
+    _MODELS_WITH_DEVICE_MAP_AUTO_EXCLUSION,
     add_left_padding,
     generate_merged_ids,
     get_context_len,
@@ -87,7 +88,8 @@ def load_pretrained_from_config(
         # Apply quanitzation configuration at model load time
         load_kwargs["torch_dtype"] = getattr(torch, config_obj.quantization.bnb_4bit_compute_dtype)
         load_kwargs["quantization_config"] = config_obj.quantization.to_bitsandbytes()
-        load_kwargs["device_map"] = "auto"
+        if config_obj.base_model not in _MODELS_WITH_DEVICE_MAP_AUTO_EXCLUSION:
+            load_kwargs["device_map"] = "auto"
 
     if config_obj.model_parameters:
         # Add any model specific parameters to the load kwargs
diff --git a/ludwig/schema/llms/base_model.py b/ludwig/schema/llms/base_model.py
index 3f48b55694a..92e510c899c 100644
--- a/ludwig/schema/llms/base_model.py
+++ b/ludwig/schema/llms/base_model.py
@@ -9,6 +9,7 @@
 from ludwig.error import ConfigValidationError
 from ludwig.schema.metadata import LLM_METADATA
 from ludwig.schema.metadata.parameter_metadata import convert_metadata_to_json
+from ludwig.utils.llm_utils import _PHI_BASE_MODEL_MAPPING
 
 # Maps a preset LLM name to the full slash-delimited HF path. If the user chooses a preset LLM, the preset LLM name is
 # replaced with the full slash-delimited HF path using this map, after JSON validation but before config object
@@ -72,6 +73,8 @@ def validate(model_name: str):
                 return MODEL_PRESETS[model_name]
             if os.path.isdir(model_name):
                 return model_name
+            if model_name in _PHI_BASE_MODEL_MAPPING:
+                return _PHI_BASE_MODEL_MAPPING[model_name]
             try:
                 AutoConfig.from_pretrained(model_name)
                 return model_name
diff --git a/ludwig/schema/model_types/utils.py b/ludwig/schema/model_types/utils.py
index b8550d06838..929bb42ea5d 100644
--- a/ludwig/schema/model_types/utils.py
+++ b/ludwig/schema/model_types/utils.py
@@ -34,7 +34,7 @@
 from ludwig.schema.trainer import ECDTrainerConfig
 from ludwig.types import HyperoptConfigDict, ModelConfigDict
 from ludwig.utils.data_utils import get_sanitized_feature_name
-from ludwig.utils.llm_utils import get_context_len
+from ludwig.utils.llm_utils import _PHI_BASE_MODEL_MAPPING, get_context_len
 
 if TYPE_CHECKING:
     from ludwig.schema.model_types.base import ModelConfig
@@ -307,6 +307,9 @@ def set_llm_parameters(config: "ModelConfig") -> None:
     if config.model_type != MODEL_LLM:
         return
 
+    # Do an in-place replacement for Phi models since they don't work well out of the box
+    _replace_phi_model_with_supported_model(config)
+
     # Set preprocessing parameters for text features for LLM model type
     _set_llm_tokenizers(config)
 
@@ -314,6 +317,19 @@ def set_llm_parameters(config: "ModelConfig") -> None:
     _set_generation_max_new_tokens(config)
 
 
+def _replace_phi_model_with_supported_model(config: "ModelConfig") -> None:
+    """Replaces the phi model with a supported model that is compatible with the LLM model type."""
+    if config.base_model not in _PHI_BASE_MODEL_MAPPING:
+        return
+
+    logger.warning(
+        f"{config.base_model} does not work correctly out of the box since it requires running remote code."
+        f"Replacing {config.base_model} with {_PHI_BASE_MODEL_MAPPING[config.base_model]} as the base LLM model."
+    )
+
+    config.base_model = _PHI_BASE_MODEL_MAPPING[config.base_model]
+
+
 def _set_llm_tokenizers(config: "ModelConfig") -> None:
     """Sets the tokenizers for the LLM model to the pretrained model name or path. This ensures that they use the
     correct shared vocabulary from the tokenizer.
diff --git a/ludwig/utils/llm_utils.py b/ludwig/utils/llm_utils.py
index 9a0a65bd79f..77ab4c5f63e 100644
--- a/ludwig/utils/llm_utils.py
+++ b/ludwig/utils/llm_utils.py
@@ -18,6 +18,16 @@
 
 FALLBACK_CONTEXT_LEN = 2048
 
+# The official microsoft phi models don't work out of the box because the weights aren't compatiable with HF
+# See https://github.com/huggingface/transformers/issues/28049 for more context.
+_PHI_BASE_MODEL_MAPPING = {
+    "microsoft/phi-1": "susnato/phi-1_dev",
+    "microsoft/phi-1.5": "susnato/phi-1_5_dev",
+}
+
+# The susnato Phi models as of Transformers 4.36.1 don't support "device_map='auto'" at model load time.
+_MODELS_WITH_DEVICE_MAP_AUTO_EXCLUSION = {"susnato/phi-1_dev", "susnato/phi-1_5_dev"}
+
 
 def to_device(
     model: PreTrainedModel,
@@ -54,11 +64,13 @@ def to_device(
         model_kwargs.update(
             dict(
                 low_cpu_mem_usage=True,
-                device_map="auto",
                 max_memory={i: "13GiB" for i in range(num_gpus)},
             )
         )
 
+        if config_obj.base_model not in _MODELS_WITH_DEVICE_MAP_AUTO_EXCLUSION:
+            model_kwargs["device_map"] = "auto"
+
         if config_obj.quantization:
             model_kwargs["quantization_config"] = config_obj.quantization.to_bitsandbytes()