consolidate installation docs

rapidsai · Sep 9, 2024 · a6b2659 · a6b2659
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diff --git a/README.md b/README.md
@@ -145,7 +145,6 @@ Please see the [Demo Docker Repository](https://hub.docker.com/r/rapidsai/rapids
 ### CUDA/GPU requirements
 
 - CUDA 11.2+
-- NVIDIA driver 450.80.02+
 - Pascal architecture or better (Compute Capability >=6.0)
 
 ### Conda
@@ -155,9 +154,9 @@ cuxfilter can be installed with conda ([miniconda](https://conda.io/miniconda.ht
 For nightly version `cuxfilter version == 24.10` :
 
 ```bash
-# for CUDA 12.0
+# for CUDA 12.5
 conda install -c rapidsai-nightly -c conda-forge -c nvidia \
-    cuxfilter=24.10 python=3.12 cuda-version=12.0
+    cuxfilter=24.10 python=3.12 cuda-version=12.5
 
 # for CUDA 11.8
 conda install -c rapidsai-nightly -c conda-forge -c nvidia \
@@ -178,6 +177,8 @@ conda install -c rapidsai -c conda-forge -c nvidia \
 
 Note: cuxfilter is supported only on Linux, and with Python versions 3.10, 3.11, and 3.12.
 
+> Above are sample install snippets for cuxfilter, see the [Get RAPIDS version picker](https://rapids.ai/start.html) for installing the latest `cuxfilter` version.
+
 ### PyPI
 
 Install cuxfilter from PyPI using pip:

diff --git a/notebooks/README.md b/notebooks/README.md
@@ -32,21 +32,14 @@ These are example notebooks to showcase cuxfilter with [cuDF](https://github.com
 
 Once you have registered with your email address, simply sign in to your account, start a CPU or GPU runtime, and open your project - all in your browser.
 
-To setup a rapids environment in studio lab(you only need to do this the first time, since studio lab has 15GB of persistent storage across sessions), open a new terminal:
+To setup a RAPIDS environment in studio lab (you only need to do this the first time, since studio lab has 15GB of persistent storage across sessions),
+open a new terminal and run the following
 
 ```bash
 conda install ipykernel
-
-# for stable rapids version
-conda install -c rapidsai -c numba -c conda-forge -c nvidia \
-    cuxfilter python=3.12 cudatoolkit=11.8
-
-# for nightly rapids version
-conda install -c rapidsai-nightly -c numba -c conda-forge -c nvidia \
-    cuxfilter python=3.12 cudatoolkit=11.8
 ```
 
-> Above are sample install snippets for cuxfilter, see the [Get RAPIDS version picker](https://rapids.ai/start.html) for installing the latest `cuxfilter` version.
+Then install `cuxfilter` and its dependencies by following the instructions in ["Installation"](../README.md#installation) in the project's main README.
 
 Once installed, you should see a card in the launcher for that environment and kernel after about a minute.