Fixing the failure of models without max_position_embeddings attribute. (#27499)

fix max pos issue

Co-authored-by: Adam Louly <adamlouly@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

examples/pytorch/language-modeling/run_clm.py

@@ -497,15 +497,20 @@ def main():
                 batched=True,
                 remove_columns=column_names,
             )
+    if hasattr(config, "max_position_embeddings"):
+        max_pos_embeddings = config.max_position_embeddings
+    else:
+        # Define a default value if the attribute is missing in the config.
+        max_pos_embeddings = 1024
 
     if data_args.block_size is None:
         block_size = tokenizer.model_max_length
-        if block_size > config.max_position_embeddings:
+        if block_size > max_pos_embeddings:
             logger.warning(
                 f"The tokenizer picked seems to have a very large `model_max_length` ({tokenizer.model_max_length}). "
-                f"Using block_size={min(1024, config.max_position_embeddings)} instead. You can change that default value by passing --block_size xxx."
+                f"Using block_size={min(1024, max_pos_embeddings)} instead. You can change that default value by passing --block_size xxx."
             )
-            block_size = min(1024, config.max_position_embeddings)
+            block_size = min(1024, max_pos_embeddings)
     else:
         if data_args.block_size > tokenizer.model_max_length:
             logger.warning(