You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: docs/source/installation.mdx
+8-8Lines changed: 8 additions & 8 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -19,7 +19,7 @@ Welcome to the installation guide for the `bitsandbytes` library! This document
19
19
20
20
## CUDA[[cuda]]
21
21
22
-
`bitsandbytes` is currently only supported on CUDA GPUs for CUDA versions **11.0 - 12.5**. However, there's an ongoing multi-backend effort under development, which is currently in alpha. If you're interested in providing feedback or testing, check out [the multi-backend section below](#multi-backend).
22
+
`bitsandbytes` is currently only supported on CUDA GPUs for CUDA versions **11.0 - 12.6**. However, there's an ongoing multi-backend effort under development, which is currently in alpha. If you're interested in providing feedback or testing, check out [the multi-backend section below](#multi-backend).
23
23
24
24
### Supported CUDA Configurations[[cuda-pip]]
25
25
@@ -29,7 +29,7 @@ The latest version of `bitsandbytes` builds on the following configurations:
For Linux systems, ensure your hardware meets the following requirements:
35
35
@@ -115,7 +115,7 @@ pip install -e . # `-e` for "editable" install, when developing BNB (otherwise
115
115
116
116
Windows systems require Visual Studio with C++ support as well as an installation of the CUDA SDK.
117
117
118
-
To compile from source, you need CMake >= **3.22.1** and Python >= **3.8** installed. You should also install CUDA Toolkit by following the [CUDA Installation Guide for Windows](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html) guide from NVIDIA.
118
+
To compile from source, you need CMake >= **3.22.1** and Python >= **3.9** installed. You should also install CUDA Toolkit by following the [CUDA Installation Guide for Windows](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html) guide from NVIDIA.
119
119
120
120
Refer to the following table if you're using another CUDA Toolkit version.
121
121
@@ -150,12 +150,12 @@ Then locally install the CUDA version you need with this script from bitsandbyte
3. Now when you launch bitsandbytes with these environment variables, the PyTorch CUDA version is overridden by the new CUDA version (in this example, version 11.7) and a different bitsandbytes library is loaded.
0 commit comments