[Cherry-Pick][Fix] Inferring a default sequence length during transformers export

src/sparseml/transformers/export.py

@@ -297,10 +297,20 @@ def export_transformer_to_onnx(
     )
 
     if sequence_length is None:
+        if hasattr(config, "max_position_embeddings"):
+            sequence_length = config.max_position_embeddings
+        elif hasattr(config, "max_seq_len"):
+            sequence_length = config.max_seq_len
+        else:
+            raise ValueError(
+                "Could not infer a default sequence length "
+                "from the HF transformers config. Please specify "
+                "the sequence length with --sequence_length"
+            )
         _LOGGER.info(
-            f"Using default sequence length of {config.max_position_embeddings}"
+            f"Using default sequence length of {sequence_length} "
+            "(inferred from HF transformers config) "
         )
-        sequence_length = config.max_position_embeddings
 
     tokenizer = AutoTokenizer.from_pretrained(
         model_path, model_max_length=sequence_length