Update README.md

README.md

@@ -9,9 +9,7 @@ library_name: transformers
 
 Correct conversion to Hugging Face format of the https://huggingface.co/AntonV/mamba2-370m-hf model. This fixes the error that occurs during saving the weights:
 
-```python
-RuntimeError: The weights trying to be saved contained shared tensors [{'backbone.embeddings.weight', 'lm_head.weight'}] that are mismatching the transformers base configuration. Try saving using `safe_serialization=False` or remove this tensor sharing.
-```
+**RuntimeError: The weights trying to be saved contained shared tensors [{'backbone.embeddings.weight', 'lm_head.weight'}] that are mismatching the transformers base configuration. Try saving using `safe_serialization=False` or remove this tensor sharing.**
 
 ## Usage
 ```python
@@ -27,9 +25,7 @@ print(tokenizer.batch_decode(out))
 
 This doesn't fix the Mamba2 cache error during evaluation in SFTTrainer:
 
-```python
-TypeError: Unsupported types (<class 'transformers.models.mamba2.modeling_mamba2.Mamba2Cache'>) passed to `_pad_across_processes`. Only nested list/tuple/dicts of objects that are valid for `is_torch_tensor` should be passed.
-```
+**TypeError: Unsupported types (<class 'transformers.models.mamba2.modeling_mamba2.Mamba2Cache'>) passed to `_pad_across_processes`. Only nested list/tuple/dicts of objects that are valid for `is_torch_tensor` should be passed.**
 
 A temporary fix is disabling the usage of the cache: