diff --git a/byaldi/colpali.py b/byaldi/colpali.py
index cc11dcb..40c24fc 100644
--- a/byaldi/colpali.py
+++ b/byaldi/colpali.py
@@ -7,7 +7,7 @@
 
 import srsly
 import torch
-from colpali_engine.models import ColPali, ColPaliProcessor, ColQwen2, ColQwen2Processor
+from colpali_engine.models import ColPali, ColPaliProcessor, ColQwen2, ColQwen2Processor, ColQwen2_5, ColQwen2_5_Processor
 from pdf2image import convert_from_path
 from PIL import Image
 
@@ -35,6 +35,7 @@ def __init__(
         if (
             "colpali" not in pretrained_model_name_or_path.lower()
             and "colqwen2" not in pretrained_model_name_or_path.lower()
+            and "colqwen2.5" not in pretrained_model_name_or_path.lower()
         ):
             raise ValueError(
                 "This pre-release version of Byaldi only supports ColPali and ColQwen2 for now. Incorrect model name specified."
@@ -77,6 +78,18 @@ def __init__(
                 ),
                 token=kwargs.get("hf_token", None) or os.environ.get("HF_TOKEN"),
             )
+        elif "colqwen2.5" in pretrained_model_name_or_path.lower():
+            self.model = ColQwen2_5.from_pretrained(
+                self.pretrained_model_name_or_path,
+                torch_dtype=torch.bfloat16,
+                device_map=(
+                    "cuda"
+                    if device == "cuda"
+                    or (isinstance(device, torch.device) and device.type == "cuda")
+                    else None
+                ),
+                token=kwargs.get("hf_token", None) or os.environ.get("HF_TOKEN"),
+            )    
         elif "colqwen2" in pretrained_model_name_or_path.lower():
             self.model = ColQwen2.from_pretrained(
                 self.pretrained_model_name_or_path,
@@ -99,6 +112,14 @@ def __init__(
                     token=kwargs.get("hf_token", None) or os.environ.get("HF_TOKEN"),
                 ),
             )
+        elif "colqwen2.5" in pretrained_model_name_or_path.lower():
+            self.processor = cast(
+                ColQwen2_5_Processor,
+                ColQwen2_5_Processor.from_pretrained(
+                    self.pretrained_model_name_or_path,
+                    token=kwargs.get("hf_token", None) or os.environ.get("HF_TOKEN"),
+                ),
+            )
         elif "colqwen2" in pretrained_model_name_or_path.lower():
             self.processor = cast(
                 ColQwen2Processor,
@@ -742,3 +763,4 @@ def encode_query(self, query: Union[str, List[str]]) -> torch.Tensor:
 
     def get_doc_ids_to_file_names(self):
         return self.doc_ids_to_file_names
+