Merge pull request #561 from patrickvonplaten/add_installation

Improve installation section and "get started"
This commit is contained in:
Nicolas Patry
2023-08-24 16:25:52 +02:00
committed by GitHub
2 changed files with 70 additions and 13 deletions

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@ -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).
```rust
let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
## Get started
let c = a.matmul(&b)?;
println!("{c}");
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
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]`.
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/):