Fix add-new-model-like when old model checkpoint is not found (#15805)

* Fix add-new-model-like command when old checkpoint can't be recovered

* Style

src/transformers/commands/add_new_model_like.py

@@ -1115,6 +1115,7 @@ def create_new_model_like(
     new_model_patterns: ModelPatterns,
     add_copied_from: bool = True,
     frameworks: Optional[List[str]] = None,
+    old_checkpoint: Optional[str] = None,
 ):
     """
     Creates a new model module like a given model of the Transformers library.
@@ -1126,11 +1127,22 @@ def create_new_model_like(
             Whether or not to add "Copied from" statements to all classes in the new model modeling files.
         frameworks (`List[str]`, *optional*):
             If passed, will limit the duplicate to the frameworks specified.
+        old_checkpoint (`str`, *optional*):
+            The name of the base checkpoint for the old model. Should be passed along when it can't be automatically
+            recovered from the `model_type`.
     """
     # Retrieve all the old model info.
     model_info = retrieve_info_for_model(model_type, frameworks=frameworks)
     model_files = model_info["model_files"]
     old_model_patterns = model_info["model_patterns"]
+    if old_checkpoint is not None:
+        old_model_patterns.checkpoint = old_checkpoint
+    if len(old_model_patterns.checkpoint) == 0:
+        raise ValueError(
+            "The old model checkpoint could not be recovered from the model type. Please pass it to the "
+            "`old_checkpoint` argument."
+        )
+
     keep_old_processing = True
     for processing_attr in ["feature_extractor_class", "processor_class", "tokenizer_class"]:
         if getattr(old_model_patterns, processing_attr) != getattr(new_model_patterns, processing_attr):
@@ -1291,8 +1303,15 @@ class AddNewModelLikeCommand(BaseTransformersCLICommand):
             self.model_patterns = ModelPatterns(**config["new_model_patterns"])
             self.add_copied_from = config.get("add_copied_from", True)
             self.frameworks = config.get("frameworks", ["pt", "tf", "flax"])
+            self.old_checkpoint = config.get("old_checkpoint", None)
         else:
-            self.old_model_type, self.model_patterns, self.add_copied_from, self.frameworks = get_user_input()
+            (
+                self.old_model_type,
+                self.model_patterns,
+                self.add_copied_from,
+                self.frameworks,
+                self.old_checkpoint,
+            ) = get_user_input()
 
         self.path_to_repo = path_to_repo
 
@@ -1310,6 +1329,7 @@ class AddNewModelLikeCommand(BaseTransformersCLICommand):
             new_model_patterns=self.model_patterns,
             add_copied_from=self.add_copied_from,
             frameworks=self.frameworks,
+            old_checkpoint=self.old_checkpoint,
         )
 
 
@@ -1402,6 +1422,12 @@ def get_user_input():
     old_processor_class = old_model_info["model_patterns"].processor_class
     old_frameworks = old_model_info["frameworks"]
 
+    old_checkpoint = None
+    if len(old_model_info["model_patterns"].checkpoint) == 0:
+        old_checkpoint = get_user_field(
+            "We couldn't find the name of the base checkpoint for that model, please enter it here."
+        )
+
     model_name = get_user_field("What is the name for your new model?")
     default_patterns = ModelPatterns(model_name, model_name)
 
@@ -1497,4 +1523,4 @@ def get_user_input():
         )
         frameworks = list(set(frameworks.split(" ")))
 
-    return (old_model_type, model_patterns, add_copied_from, frameworks)
+    return (old_model_type, model_patterns, add_copied_from, frameworks, old_checkpoint)