From fc39ff3ab08dde8af5a1efd46b65a9f46d322fe0 Mon Sep 17 00:00:00 2001 From: Alex Czar <AlexCzar@users.noreply.github.com> Date: Fri, 17 Nov 2023 02:16:25 +0100 Subject: [PATCH] Fix typos and grammar in README.md --- README.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index ec4315d9..05be4744 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ machines without one. Run it with OpenCL or CUDA. Credit goes to [Collenchyma][collenchyma] and Rust. Leaf is part of the [Autumn][autumn] Machine Intelligence Platform, which is -working on making AI algorithms 100x more computational efficient. +working on making AI algorithms 100x more computationally efficient. We see Leaf as the core of constructing high-performance machine intelligence applications. Leaf's design makes it easy to publish independent modules to make @@ -40,7 +40,7 @@ deployment easily accessible for everyone. > Disclaimer: Leaf is currently in an early stage of development. > If you are experiencing any bugs with features that have been -> implemented, feel free to create a issue. +> implemented, feel free to create an issue. ## Getting Started @@ -48,7 +48,7 @@ deployment easily accessible for everyone. To learn how to build classical, deep or hybrid machine learning applications with Leaf, check out the [Leaf - Machine Learning for Hackers][leaf-book] book. -For additional information see the [Rust API Documentation][documentation] or the [Autumn Website][autumn]. +For additional information, see the [Rust API Documentation][documentation] or the [Autumn Website][autumn]. Or start by running the **Leaf examples**. @@ -58,8 +58,8 @@ a CLI for easy usage and has a detailed guide in the [project README.md][leaf-examples]. Leaf comes with an examples directory as well, which features popular neural -networks (e.g. Alexnet, Overfeat, VGG). To run them on your machine, just follow -the install guide, clone this repoistory and then run +networks (e.g. Alexnet, Overfeat, VGG). To run them on your machine, follow +the installation guide, clone this repository and then run ```bash # The examples currently require CUDA support. @@ -70,10 +70,10 @@ cargo run --release --no-default-features --features cuda --example benchmarks a ### Installation -> Leaf is build in [Rust][rust]. If you are new to Rust you can install Rust as detailed [here][rust_download]. +> Leaf is built in [Rust][rust]. If you are new to Rust, you can install Rust as detailed [here][rust_download]. We also recommend taking a look at the [official Rust - Getting Started Guide][rust_getting_started]. -To start building a machine learning application (Rust only for now. Wrappers are welcome) and you are using Cargo, just add Leaf to your `Cargo.toml`: +To start building a machine learning application (Rust only for now, wrappers are welcome), and you are using Cargo, just add Leaf to your `Cargo.toml`: ```toml [dependencies] @@ -84,8 +84,8 @@ leaf = "0.2.1" [rust_getting_started]: https://doc.rust-lang.org/book/getting-started.html [cargo-edit]: https://github.com/killercup/cargo-edit -If you are on a machine that doesn't have support for CUDA or OpenCL you -can selectively enable them like this in your `Cargo.toml`: +If you are on a machine that doesn't have support for CUDA or OpenCL, you +can selectively enable them in your `Cargo.toml`: ```toml [dependencies] @@ -103,15 +103,15 @@ opencl = ["leaf/opencl"] ### Contributing If you want to start hacking on Leaf (e.g. - [adding a new `Layer`](http://autumnai.com/leaf/book/create-new-layer.html)) +[adding a new `Layer`](http://autumnai.com/leaf/book/create-new-layer.html)) you should start with forking and cloning the repository. We have more instructions to help you get started in the [CONTRIBUTING.md][contributing]. -We also has a near real-time collaboration culture, which happens -here on Github and on the [Leaf Gitter Channel][gitter-leaf]. +We also have a near real-time collaboration culture, which happens +here on GitHub and on the [Leaf Gitter Channel][gitter-leaf]. -> Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as below, without any additional terms or conditions. +> Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual-licensed as below, without any additional terms or conditions. [contributing]: CONTRIBUTING.md [gitter-leaf]: https://gitter.im/autumnai/leaf @@ -134,7 +134,7 @@ and extensible as possible. More helpful crates you can use with Leaf: - With a bit of luck, you can find us online on the #rust-machine-learning IRC at irc.mozilla.org, - but we are always approachable on [Gitter/Leaf][gitter-leaf] -- For bugs and feature request, you can create a [Github issue][leaf-issue] +- For bugs and feature request, you can create a [GitHub issue][leaf-issue] - For more private matters, send us email straight to our inbox: developers@autumnai.com - Refer to [Autumn][autumn] for more information @@ -151,7 +151,7 @@ You can find the release history at the [CHANGELOG.md][changelog]. We are using Licensed under either of - * Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0) - * MIT license ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT) +* Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0) +* MIT license ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT) at your option.