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Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 23 |
1 files changed, 12 insertions, 11 deletions
@@ -2,10 +2,11 @@ ML framework for Rust ```rust -let a = Tensor::zeros((2, 3), DType::F32, &Device::Cpu)?; -let b = Tensor::zeros((3, 4), DType::F32, &Device::Cpu)?; +let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?; +let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?; let c = a.matmul(&b)?; +println!("{c}"); ``` ## Check out our examples @@ -45,13 +46,15 @@ And then browse to ## Features -- Simple syntax (looks and like PyTorch) -- CPU and Cuda backends, m1, f16, bf16 (and tentatively wasm) +- Simple syntax, looks and like PyTorch. +- CPU and Cuda backends, m1, f16, bf16. - Enable serverless (CPU), small and fast deployments -- Model training -- Distributed computing (NCCL). -- Models out of the box (Llama, Whisper, Falcon, ...) -- Emphasis on enabling users to use custom ops/kernels +- WASM support, run your models in a browser. +- Model training. +- Distributed computing using NCCL. +- Models out of the box: Llama, Whisper, Falcon, BERT... +- Embed user-defined ops/kernels, such as [flash-attention + v2](https://github.com/LaurentMazare/candle/blob/89ba005962495f2bfbda286e185e9c3c7f5300a3/candle-flash-attn/src/lib.rs#L152). ## How to use ? @@ -59,9 +62,7 @@ Cheatsheet: | | Using PyTorch | Using Candle | |------------|------------------------------------------|------------------------------------------------------------------| -| Creation | `torch.Tensor([[1, 2], [3, 4]])` | `Tensor::new(` | -| | | ` &[[1f32, 2.]], [3., 4.]],` | -| | | ` &Device::Cpu)?` | +| Creation | `torch.Tensor([[1, 2], [3, 4]])` | `Tensor::new(&[[1f32, 2.]], [3., 4.]], &Device::Cpu)?` | | Indexing | `tensor[:, :4]` | `tensor.i((.., ..4))?` | | Operations | `tensor.view((2, 2))` | `tensor.reshape((2, 2))?` | | Operations | `a.matmul(b)` | `a.matmul(&b)?` | |