docs: update

docs/pages/migrating/v2.mdx

@@ -71,7 +71,7 @@ let (raw_shape, raw_data) = tensor.extract_raw_tensor_mut();
 You can now create a tensor on device memory with `Tensor::new` & an allocator:
 
 ```rust
-let allocator = Allocator::new(&session, MemoryInfo::new(AllocationDevice::CUDAPinned, 0, AllocatorType::Device, MemoryType::CPUInput)?)?;
+let allocator = Allocator::new(&session, MemoryInfo::new(AllocationDevice::CUDA_PINNED, 0, AllocatorType::Device, MemoryType::CPUInput)?)?;
 let tensor = Tensor::<f32>::new(&allocator, [1, 128, 128, 3])?;
 ```
 

docs/pages/perf/execution-providers.mdx

@@ -196,9 +196,7 @@ If it seems like the execution provider is not registering properly, or you are
 ## Notes
 
 ### CUDA
-`ort` provides binaries for both CUDA 11 and CUDA 12; `ort` will automatically choose which binary to install based on whether CUDA 12 is installed.
-
-CUDA 11 requires cuDNN 8.x. CUDA 12 requires cuDNN 9.x. Make sure the correct version of cuDNN is installed and available on the `PATH`.
+`ort` provides binaries for CUDA 12 with cuDNN 9.x only. Make sure the correct version of CUDA & cuDNN are installed and available on the `PATH`.
 
 ### CoreML
 Statically linking to CoreML (the default behavior when using downloaded binaries + the `coreml` Cargo feature) requires an additional Rust flag in order to link properly. You'll need to provide the flag `-C link-arg=-fapple-link-rtlib` to `rustc`. You can do this via an entry in [`.cargo/config.toml`](https://doc.rust-lang.org/cargo/reference/config.html#hierarchical-structure), in a build script, or in an environment variable.