diff --git a/docs/index.md b/docs/index.md
index ff6ab5ed6e..82023371f0 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -30,7 +30,7 @@ If you are migrating from PyTorch, welcome. Most of the API is the same. We hope
 
 ### tinygrad doesn't have nn.Module
 
-There's nothing special about a "Module" class in tinygrad, it's just a normal class. [`nn.state.get_parameters`](nn/#tinygrad.nn.state.get_parameters) can be used to recursively search normal claases for valid tensors. Instead of the `forward` method in PyTorch, tinygrad just uses `__call__`
+There's nothing special about a "Module" class in tinygrad, it's just a normal class. [`nn.state.get_parameters`](nn/#tinygrad.nn.state.get_parameters) can be used to recursively search normal classes for valid tensors. Instead of the `forward` method in PyTorch, tinygrad just uses `__call__`
 
 ### tinygrad is functional
 
@@ -42,4 +42,4 @@ When you do `a+b` in tinygrad, nothing happens. It's not until you [`realize`](t
 
 ### tinygrad requires @TinyJIT to be fast
 
-PyTorch spends a lot of development effort to make dispatch very fast. tinygrad doesn't. We have a simple decorator that will replay the kernels used in the decorated function.
\ No newline at end of file
+PyTorch spends a lot of development effort to make dispatch very fast. tinygrad doesn't. We have a simple decorator that will replay the kernels used in the decorated function.