Prettier

`npx prettier --write --prose-wrap always README.md`

README.md

@@ -8,23 +8,28 @@
 ![MIT/Apache2](https://shields.io/badge/license-MIT%2FApache--2.0-blue)
 [![Discord](https://img.shields.io/discord/1085885067601137734)](https://discord.gg/YB9WaXYAWU)
 
-`llm` is a Rust ecosystem of libraries for running inference on large language models, inspired by [llama.cpp](https://github.com/ggerganov/llama.cpp).
+`llm` is a Rust ecosystem of libraries for running inference on large language
+models, inspired by [llama.cpp](https://github.com/ggerganov/llama.cpp).
 
-The primary crate is the `llm` crate, which wraps `llm-base` and supported model crates. This is used by `llm-cli` to provide inference for all supported models.
+The primary crate is the `llm` crate, which wraps `llm-base` and supported model
+crates. This is used by `llm-cli` to provide inference for all supported models.
 
-It is powered by the [`ggml`](https://github.com/ggerganov/ggml) tensor library, and aims to bring
-the robustness and ease of use of Rust to the world of large language models.
+It is powered by the [`ggml`](https://github.com/ggerganov/ggml) tensor library,
+and aims to bring the robustness and ease of use of Rust to the world of large
+language models.
 
 ## Getting started
 
 Make sure you have a Rust 1.65.0 or above and C toolchain[^1] set up.
 
-`llm` is a Rust library that re-exports `llm-base` and the model crates (e.g. `bloom`, `gpt2` `llama`).
+`llm` is a Rust library that re-exports `llm-base` and the model crates (e.g.
+`bloom`, `gpt2` `llama`).
 
-`llm-cli` (binary name `llm`) is a basic application that provides a CLI interface to the library.
+`llm-cli` (binary name `llm`) is a basic application that provides a CLI
+interface to the library.
 
-**NOTE**: For best results, make sure to build and run in release mode.
-Debug builds are going to be very slow.
+**NOTE**: For best results, make sure to build and run in release mode. Debug
+builds are going to be very slow.
 
 ### Building using `cargo`
 
@@ -34,8 +39,8 @@ Run
 cargo install --git https://github.com/rustformers/llm llm-cli
 ```
 
-to install `llm` to your Cargo `bin` directory, which `rustup` is likely to
-have added to your `PATH`.
+to install `llm` to your Cargo `bin` directory, which `rustup` is likely to have
+added to your `PATH`.
 
 The CLI application can then be run through `llm`.
 
@@ -68,7 +73,8 @@ GGML files are easy to acquire. Currently, the following models are supported:
 - [GPT-J](https://huggingface.co/docs/transformers/model_doc/gptj)
 - [LLaMA](https://huggingface.co/docs/transformers/model_doc/llama)
 - [GPT-NeoX](https://huggingface.co/docs/transformers/model_doc/gpt_neox)
-- [BLOOM](https://huggingface.co/docs/transformers/model_doc/bloom) (partial support, results inconsistent)
+- [BLOOM](https://huggingface.co/docs/transformers/model_doc/bloom) (partial
+  support, results inconsistent)
 
 Certain older GGML formats are not supported by this project, but the goal is to
 maintain feature parity with the upstream GGML project. For problems relating to
@@ -78,18 +84,22 @@ loading models, or requesting support for
 
 #### From Hugging Face
 
-Hugging Face 🤗 is a leader in open-source machine learning and hosts hundreds of GGML models.
+Hugging Face 🤗 is a leader in open-source machine learning and hosts hundreds
+of GGML models.
 [Search for GGML models on Hugging Face 🤗](https://huggingface.co/models?search=ggml).
 
 #### r/LocalLLaMA
 
-This Reddit community maintains [a wiki](https://www.reddit.com/r/LocalLLaMA/wiki/index/)
-related to GGML models, including well organized lists of links for acquiring
-[GGML models](https://www.reddit.com/r/LocalLLaMA/wiki/models/) (mostly from Hugging Face 🤗).
+This Reddit community maintains
+[a wiki](https://www.reddit.com/r/LocalLLaMA/wiki/index/) related to GGML
+models, including well organized lists of links for acquiring
+[GGML models](https://www.reddit.com/r/LocalLLaMA/wiki/models/) (mostly from
+Hugging Face 🤗).
 
 #### LLaMA original weights
 
-Currently, the only legal source to get the original weights is [this repository](https://github.com/facebookresearch/llama/blob/main/README.md#llama).
+Currently, the only legal source to get the original weights is
+[this repository](https://github.com/facebookresearch/llama/blob/main/README.md#llama).
 
 After acquiring the weights, it is necessary to convert them into a format that
 is compatible with ggml. To achieve this, follow the steps outlined below:
@@ -133,12 +143,13 @@ Some additional things to try:
   ![Gif showcasing alpaca repl mode](./doc/resources/alpaca_repl_screencap.gif)
 
 - Sessions can be loaded (`--load-session`) or saved (`--save-session`) to file.
-  To automatically load and save the same session, use `--persist-session`.
-  This can be used to cache prompts to reduce load time, too:
+  To automatically load and save the same session, use `--persist-session`. This
+  can be used to cache prompts to reduce load time, too:
 
   ![Gif showcasing prompt caching](./doc/resources/prompt_caching_screencap.gif)
 
-  (This GIF shows an older version of the flags, but the mechanics are still the same.)
+  (This GIF shows an older version of the flags, but the mechanics are still the
+  same.)
 
 [^1]:
     A modern-ish C toolchain is required to compile `ggml`. A C++ toolchain
@@ -161,46 +172,44 @@ docker run --rm --name llm -it -v ${PWD}/data:/data -v ${PWD}/examples:/examples
 
 ### Why did you do this?
 
-It was not my choice. Ferris appeared to me in my dreams and asked me
-to rewrite this in the name of the Holy crab.
+It was not my choice. Ferris appeared to me in my dreams and asked me to rewrite
+this in the name of the Holy crab.
 
 ### Seriously now.
 
-Come on! I don't want to get into a flame war. You know how it goes,
-_something something_ memory _something something_ cargo is nice, don't make
-me say it, everybody knows this already.
+Come on! I don't want to get into a flame war. You know how it goes, _something
+something_ memory _something something_ cargo is nice, don't make me say it,
+everybody knows this already.
 
 ### I insist.
 
-_Sheesh! Okaaay_. After seeing the huge potential for **llama.cpp**,
-the first thing I did was to see how hard would it be to turn it into a
-library to embed in my projects. I started digging into the code, and realized
-the heavy lifting is done by `ggml` (a C library, easy to bind to Rust) and
-the whole project was just around ~2k lines of C++ code (not so easy to bind).
-After a couple of (failed) attempts to build an HTTP server into the tool, I
-realized I'd be much more productive if I just ported the code to Rust, where
-I'm more comfortable.
+_Sheesh! Okaaay_. After seeing the huge potential for **llama.cpp**, the first
+thing I did was to see how hard would it be to turn it into a library to embed
+in my projects. I started digging into the code, and realized the heavy lifting
+is done by `ggml` (a C library, easy to bind to Rust) and the whole project was
+just around ~2k lines of C++ code (not so easy to bind). After a couple of
+(failed) attempts to build an HTTP server into the tool, I realized I'd be much
+more productive if I just ported the code to Rust, where I'm more comfortable.
 
 ### Is this the real reason?
 
-Haha. Of course _not_. I just like collecting imaginary internet
-points, in the form of little stars, that people seem to give to me whenever I
-embark on pointless quests for _rewriting X thing, but in Rust_.
+Haha. Of course _not_. I just like collecting imaginary internet points, in the
+form of little stars, that people seem to give to me whenever I embark on
+pointless quests for _rewriting X thing, but in Rust_.
 
 ### How is this different from `llama.cpp`?
 
 This is a reimplementation of `llama.cpp` that does not share any code with it
 outside of `ggml`. This was done for a variety of reasons:
 
 - `llama.cpp` requires a C++ compiler, which can cause problems for
-  cross-compilation to more esoteric platforms. An example of such a platform
-  is WebAssembly, which can require a non-standard compiler SDK.
-- Rust is easier to work with from a development and open-source perspective;
-  it offers better tooling for writing "code in the large" with many other
-  authors. Additionally, we can benefit from the larger Rust ecosystem with
-  ease.
-- We would like to make `ggml` an optional backend
-  (see [this issue](https://github.com/rustformers/llm/issues/31)).
-
-In general, we hope to build a solution for model inferencing that is as easy
-to use and deploy as any other Rust crate.
+  cross-compilation to more esoteric platforms. An example of such a platform is
+  WebAssembly, which can require a non-standard compiler SDK.
+- Rust is easier to work with from a development and open-source perspective; it
+  offers better tooling for writing "code in the large" with many other authors.
+  Additionally, we can benefit from the larger Rust ecosystem with ease.
+- We would like to make `ggml` an optional backend (see
+  [this issue](https://github.com/rustformers/llm/issues/31)).
+
+In general, we hope to build a solution for model inferencing that is as easy to
+use and deploy as any other Rust crate.