diff --git a/src/axolotl/processing_strategies.py b/src/axolotl/processing_strategies.py
index 0b854af8dc..a7fa533f58 100644
--- a/src/axolotl/processing_strategies.py
+++ b/src/axolotl/processing_strategies.py
@@ -1,5 +1,6 @@
 """Module containing ProcessingStrategy classes and its derivative for different MultiModal Model types"""
 
+import ast
 from copy import deepcopy
 from typing import Optional
 
@@ -75,6 +76,49 @@ def convert_legacy_format(example: dict) -> dict:
             result["messages"] = messages
             return result
 
+        def convert_multiple_choice_to_multimedia_messages(
+            messages: dict,
+        ) -> list[dict]:
+
+            def construct_prompt(sample):
+                question = sample["question"]
+                options = sample["options"]
+                if isinstance(options, str):
+                    options = ast.literal_eval(options)
+
+                example = ""
+                start_chr = "A"
+                prediction_range = []
+                index2ans = {}
+                for option in options:
+                    prediction_range.append(start_chr)
+                    example += f"({start_chr}) {option}\n"
+                    index2ans[start_chr] = option
+                    start_chr = chr(ord(start_chr) + 1)
+
+                empty_prompt_sample_structure = "{}\n\n{}\n\nAnswer with the option's letter from the given choices directly."
+                empty_prompt = empty_prompt_sample_structure.format(question, example)
+
+                return empty_prompt
+
+            new_messages = []
+
+            user_content = construct_prompt(messages)
+            assistant_response = messages["answer"]
+
+            new_messages.append(
+                {"role": "user", "content": [{"type": "text", "text": user_content}]}
+            )
+
+            new_messages.append(
+                {
+                    "role": "assistant",
+                    "content": [{"type": "text", "text": assistant_response}],
+                }
+            )
+
+            return new_messages
+
         def convert_messages_to_multimedia_messages(messages: list[dict]) -> list[dict]:
             """Convert regular messages format to Messages format with content type"""
 
@@ -106,39 +150,51 @@ def convert_messages_to_multimedia_messages(messages: list[dict]) -> list[dict]:
 
         processed_examples = []
         for example in examples:
-            if not ("messages" in example or "conversations" in example):
+            if not (
+                "messages" in example
+                or "conversations" in example
+                or "question" in example
+            ):
                 raise ValueError(
-                    "Only `messages` and `conversations` message keys are currently supported."
+                    "Only `messages`, `conversations`, and `question` message keys are currently supported."
                 )
 
             processed_example = None
             if "messages" in example:  # OpenAI format
                 processed_example = example
+                # convert regular messages format to Messages format with content type
+                # for compatibility with apply_chat_template
+                processed_example["messages"] = convert_messages_to_multimedia_messages(
+                    processed_example["messages"]
+                )
+            elif "question" in example:  # Multiple choice format
+                processed_example = {}
+                processed_example["messages"] = (
+                    convert_multiple_choice_to_multimedia_messages(example)
+                )
             else:  # Legacy format
                 processed_example = convert_legacy_format(example)
-
-            # convert regular messages format to Messages format with content type
-            # for compatibility with apply_chat_template
-            processed_example["messages"] = convert_messages_to_multimedia_messages(
-                processed_example["messages"]
-            )
+                processed_example["messages"] = convert_messages_to_multimedia_messages(
+                    processed_example["messages"]
+                )
 
             # find the image key if it exists
-            possible_image_keys = ["images", "image"]
-            image_key = None
-            for key in possible_image_keys:
-                if key in processed_example:
-                    image_key = key
-                    break
-
-            # if the image key exists, add the image to the first message
-            if image_key is not None:
-                # TODO: check if it's normal to be single image only for common datasets
-                # From observation, it's usually a list of single image but some datasets may have several columns for images
-                # Temporary solution: take the first image and suggest people convert their datasets to use multi-content Messages
-                image_value = processed_example[image_key][0]
-
-                # Handle image loading (Image, url, path, base64)
+
+            image_keys = []
+            for key in example.keys():
+                if "image" in key:
+                    image_keys.append(key)
+
+            for im_key in image_keys:
+                if example[im_key] is None:
+                    continue
+                if isinstance(example[im_key], list):
+                    if len(example[im_key]) == 0:
+                        continue
+                    image_value = example[im_key][0]
+                else:
+                    image_value = example[im_key]
+
                 image_value = load_image(image_value)
 
                 if self.image_size is not None:
@@ -163,33 +219,12 @@ def convert_messages_to_multimedia_messages(messages: list[dict]) -> list[dict]:
                             color=padding_color,
                         )
 
-                # Look for any image type in the first message
-                # some dataset have an {type: "image"} in the first message
-                ind_to_add = None
-
-                for i, content in enumerate(
-                    processed_example["messages"][0]["content"]
-                ):
-                    # Usually datasets created with image columns, don't have it in the messages itself
-                    if content["type"] == "image" and all(
-                        k not in content for k in ["image", "url", "path", "base64"]
-                    ):
-                        ind_to_add = i
-                        break
-
-                # If an image type is found, add the image to that index
-                if ind_to_add is not None:
-                    processed_example["messages"][0]["content"][ind_to_add][
-                        "image"
-                    ] = image_value
-                else:
-                    # if no image type is found, add it to end of the first message
-                    processed_example["messages"][0]["content"].append(
-                        {
-                            "type": "image",
-                            "image": image_value,
-                        }
-                    )
+                processed_example["messages"][0]["content"].append(
+                    {
+                        "type": "image",
+                        "image": image_value,
+                    }
+                )
 
             processed_examples.append(processed_example)