Merge pull request #561 from patrickvonplaten/add_installation

Improve installation section and "get started"

1 files changed, 29 insertions, 4 deletions

diff --git a/README.md b/README.md
index 7a1154a4..b510979a 100644
--- a/README.md
+++ b/README.md
@@ -10,14 +10,39 @@ and ease of use. Try our online demos:
 [LLaMA2](https://huggingface.co/spaces/lmz/candle-llama2),
 [yolo](https://huggingface.co/spaces/lmz/candle-yolo).
 
+## Get started
+
+Make sure that you have [`candle-core`](https://github.com/huggingface/candle/tree/main/candle-core) correctly installed as described in [**Installation**](https://huggingface.github.io/candle/guide/installation.html).
+
+Let's see how to run a simple matrix multiplication.
+Write the following to your `myapp/src/main.rs` file:
 ```rust
-let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
-let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
+use candle_core::{Device, Tensor};
+
+fn main() -> Result<(), Box<dyn std::error::Error>> {
+    let device = Device::Cpu;
+
+    let a = Tensor::randn(0f32, 1., (2, 3), &device)?;
+    let b = Tensor::randn(0f32, 1., (3, 4), &device)?;
+
+    let c = a.matmul(&b)?;
+    println!("{c}");
+    Ok(())
+}
+```
+
+`cargo run` should display a tensor of shape `Tensor[[2, 4], f32]`.
+
 
-let c = a.matmul(&b)?;
-println!("{c}");
+Having installed `candle` with Cuda support, simply define the `device` to be on GPU:
+
+```diff
+- let device = Device::Cpu;
++ let device = Device::new_cuda(0)?;
 ```
 
+For more advanced examples, please have a look at the following section.
+
 ## Check out our examples
 
 Check out our [examples](./candle-examples/examples/):