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Merge pull request #561 from patrickvonplaten/add_installation
Improve installation section and "get started"
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35
README.md
35
README.md
@ -10,14 +10,39 @@ and ease of use. Try our online demos:
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[LLaMA2](https://huggingface.co/spaces/lmz/candle-llama2),
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[yolo](https://huggingface.co/spaces/lmz/candle-yolo).
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```rust
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let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
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let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
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## Get started
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let c = a.matmul(&b)?;
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println!("{c}");
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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).
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Let's see how to run a simple matrix multiplication.
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Write the following to your `myapp/src/main.rs` file:
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```rust
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use candle_core::{Device, Tensor};
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let device = Device::Cpu;
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let a = Tensor::randn(0f32, 1., (2, 3), &device)?;
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let b = Tensor::randn(0f32, 1., (3, 4), &device)?;
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let c = a.matmul(&b)?;
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println!("{c}");
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Ok(())
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}
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```
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`cargo run` should display a tensor of shape `Tensor[[2, 4], f32]`.
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Having installed `candle` with Cuda support, simply define the `device` to be on GPU:
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```diff
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- let device = Device::Cpu;
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+ let device = Device::new_cuda(0)?;
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```
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For more advanced examples, please have a look at the following section.
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## Check out our examples
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Check out our [examples](./candle-examples/examples/):
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