Update index.rst

removed the installation and sample code snippet.

docs/cudf/source/cudf_polars/index.rst

@@ -5,47 +5,9 @@ cuDF supports an in-memory, GPU-accelerated execution engine for Python users of
 The engine supports most of the core expressions and data types as well as a growing set of more advanced dataframe manipulations 
 and data file formats. When using the GPU engine, Polars will convert expressions into an optimized query plan and determine 
 whether the plan is supported on the GPU. If it is not, the execution will transparently fall back to the standard Polars engine 
-and run on the CPU. You can install the GPU backend for Polars with a feature flag in your standard Python pip install command.
+and run on the CPU. 
 
-.. code-block:: bash
-
-   pip install polars[gpu] --extra-index-url=https://pypi.nvidia.com 
-
-GPU-based execution can be triggered by simply running ``.collect(engine="gpu")`` instead of ``.collect()``.
-
-.. code-block:: python
-
-   # Import the necessary library
-   import polars as pl
-
-   # Define the data for the LazyFrame
-   ldf = pl.LazyFrame({
-      "a": [1.242, 1.535],
-   })
-
-   print(ldf.select(pl.col("a").round(1)).collect(engine="gpu"))
-
-
-For finer control, you can pass a GPUEngine object with additional configuration parameters to the ``engine=`` parameter.
-
-.. code-block:: python
-
-   # Import the necessary library
-   import polars as pl
-
-   # Define the data for the LazyFrame
-   ldf = pl.LazyFrame({
-      "a": [1.242, 1.535],
-   })
-
-   # Configure the GPU engine with advanced settings
-   gpu_engine = pl.GPUEngine(
-      device=0,
-      raise_on_Fail=True  # Ensure the engine fails loudly if it cannot execute on the GPU
-   )
-
-   # Execute the collection with the custom GPU engine configuration
-   print(ldf.select(pl.col("a").round(1)).collect(engine=gpu_engine))
+<TO-DO: Benchmarks>
 
 Learn More
 ----------------------
@@ -59,4 +21,4 @@ Launch on Google Colab
    :width: 200px
    :target: https://nvda.ws/rapids-cudf
 
-   Take the cuDF backend for Polars for a test-drive in a free GPU-enabled notebook environment using your Google account by `launching on Colab <TBD>`_  
+   Take the cuDF backend for Polars for a test-drive in a free GPU-enabled notebook environment using your Google account by `launching on Colab <TBD>`_