zhangyiss/mlx
1
0
Fork 0
mirror of https://github.com/ml-explore/mlx.git synced 2025-08-22 04:56:41 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

spelling: notable

Browse Source 
Signed-off-by: Josh Soref <2119212+jsoref@users.noreply.github.com>
This commit is contained in:
Josh Soref 2024-01-01 22:38:20 -05:00
parent 07782096d8
commit 0219a05d1e
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
docs/src/index.rst
View File

@ -19,7 +19,7 @@ The main differences between MLX and NumPy are:
The design of MLX is inspired by frameworks like `PyTorch The design of MLX is inspired by frameworks like `PyTorch
<https://pytorch.org/>`_, `Jax <https://github.com/google/jax>`_, and <https://pytorch.org/>`_, `Jax <https://github.com/google/jax>`_, and
`ArrayFire <https://arrayfire.org/>`_. A noteable difference from these `ArrayFire <https://arrayfire.org/>`_. A notable difference from these
frameworks and MLX is the *unified memory model*. Arrays in MLX live in shared frameworks and MLX is the *unified memory model*. Arrays in MLX live in shared
memory. Operations on MLX arrays can be performed on any of the supported memory. Operations on MLX arrays can be performed on any of the supported
device types without performing data copies. Currently supported device types device types without performing data copies. Currently supported device types