fix

docs/source/optimizers.mdx

@@ -96,7 +96,7 @@ If you want to optimize some unstable parameters with 32-bit Adam and others wit
 
 For global overrides in many different places in your code you can do:
 
-```python
+```py
 import torch
 import bitsandbytes as bnb
 
@@ -120,7 +120,7 @@ mng.override_config([model.special.weight, model.also_special.weight],
 Possible options for the config override are: `betas, eps, weight_decay, lr, optim_bits, min_8bit_size, percentile_clipping, block_wise, max_unorm`
 
 For overrides for particular layers we recommend overriding locally in each module. You can do this by passing the module, the parameter, and its attribute name to the GlobalOptimManager:
-```python
+```py
 class MyModule(torch.nn.Module):
   def __init__(din, dout):
     super(MyModule, self).__init__()

docs/source/resources.mdx

@@ -30,6 +30,7 @@ Authors: Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer
   journal={arXiv preprint arXiv:2305.14314},
   year={2023}
 }
+```
 
 ## [The case for 4-bit precision: k-bit Inference Scaling Laws (Dec 2022)](https://arxiv.org/abs/2212.09720)
 Authors: Tim Dettmers, Luke Zettlemoyer