bitsandbytes-foundation · matthewdouglas · May 19, 2025 · May 19, 2025 · May 19, 2025 · May 19, 2025
diff --git a/docs/source/_toctree.yml b/docs/source/_toctree.yml
@@ -2,18 +2,15 @@
   sections:
   - local: index
     title: bitsandbytes
-  - local: quickstart
-    title: Quickstart
   - local: installation
     title: Installation
-- title: Guides
+  - local: quickstart
+    title: Quickstart
+
+- title: Usage Guides
   sections:
   - local: optimizers
     title: 8-bit optimizers
-  - local: algorithms
-    title: Algorithms
-  - local: non_cuda_backends
-    title: Non-CUDA compute backends
   - local: fsdp_qlora
     title: FSDP-QLoRA
   - local: integrations
@@ -56,7 +53,7 @@
       title: RMSprop
     - local: reference/optim/sgd
       title: SGD
-  - title: k-bit quantizers
+  - title: Modules
     sections:
     - local: reference/nn/linear8bit
       title: LLM.int8()

diff --git a/docs/source/algorithms.mdx b/docs/source/algorithms.mdx
diff --git a/docs/source/contributing.mdx b/docs/source/contributing.mdx
@@ -1,5 +1,4 @@
-# Contributors guidelines
-... still under construction ... (feel free to propose materials, `bitsandbytes` is a community project)
+# Contribution Guide
 
 ## Setup
 

diff --git a/docs/source/faqs.mdx b/docs/source/faqs.mdx
@@ -3,5 +3,3 @@
 Please submit your questions in [this Github Discussion thread](https://github.com/bitsandbytes-foundation/bitsandbytes/discussions/1013) if you feel that they will likely affect a lot of other users and that they haven't been sufficiently covered in the documentation.
 
 We'll pick the most generally applicable ones and post the QAs here or integrate them into the general documentation (also feel free to submit doc PRs, please).
-
-# ... under construction ...
diff --git a/docs/source/installation.mdx b/docs/source/installation.mdx
diff --git a/docs/source/non_cuda_backends.mdx b/docs/source/non_cuda_backends.mdx
diff --git a/docs/source/reference/functional.mdx b/docs/source/reference/functional.mdx
@@ -9,8 +9,6 @@ The `bitsandbytes.functional` API provides the low-level building blocks for the
 * For experimental or research purposes requiring non-standard quantization or performance optimizations.
 
 ## LLM.int8()
-[[autodoc]] functional.int8_double_quant
-
 [[autodoc]] functional.int8_linear_matmul
 
 [[autodoc]] functional.int8_mm_dequant
@@ -19,7 +17,6 @@ The `bitsandbytes.functional` API provides the low-level building blocks for the
 
 [[autodoc]] functional.int8_vectorwise_quant
 
-
 ## 4-bit
 [[autodoc]] functional.dequantize_4bit
 
@@ -49,5 +46,3 @@ For more details see [8-Bit Approximations for Parallelism in Deep Learning](htt
 
 ## Utility
 [[autodoc]] functional.get_ptr
-
-[[autodoc]] functional.is_on_gpu
Original file line number	Diff line number	Diff line change
Expand Up		@@ -3,5 +3,3 @@
		Please submit your questions in [this Github Discussion thread](https://github.com/bitsandbytes-foundation/bitsandbytes/discussions/1013) if you feel that they will likely affect a lot of other users and that they haven't been sufficiently covered in the documentation.

		We'll pick the most generally applicable ones and post the QAs here or integrate them into the general documentation (also feel free to submit doc PRs, please).

		# ... under construction ...