# candle-mistral: 7b LLM with Apache 2.0 licensed weights Mistral-7B-v0.1 is a pretrained generative LLM with 7 billion parameters. It outperforms all the publicly available 13b models as of 2023-09-28. Weights (and the original Python model code) are released under the permissive Apache 2.0 license. - [Blog post](https://mistral.ai/news/announcing-mistral-7b/) from Mistral announcing the model release. - [Model card](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the HuggingFace Hub. This example supports the initial model as well as a quantized variant. ## Running the example ```bash $ cargo run --example mistral --release --features cuda -- --prompt 'Write helloworld code in Rust' --sample-len 150 Generated text: Write helloworld code in Rust ============================= This is a simple example of how to write "Hello, world!" program in Rust. ## Compile and run ``bash $ cargo build --release Compiling hello-world v0.1.0 (/home/user/rust/hello-world) Finished release [optimized] target(s) in 0.26s $ ./target/release/hello-world Hello, world! `` ## Source code ``rust fn main() { println!("Hello, world!"); } `` ## License This example is released under the terms ``` ## Running the quantized version of the model ```bash $ cargo run --example mistral --features accelerate --release -- \ $ --prompt "Here is a sample quick sort implementation in rust " --quantized -n 400 avx: false, neon: true, simd128: false, f16c: false temp: 0.00 repeat-penalty: 1.10 repeat-last-n: 64 retrieved the files in 562.292µs loaded the model in 1.100323667s Here is a sample quick sort implementation in rust ``rust fn quick_sort(arr: &mut [i32]) { if arr.len() <= 1 { return; } let pivot = arr[0]; let mut left = vec![]; let mut right = vec![]; for i in 1..arr.len() { if arr[i] < pivot { left.push(arr[i]); } else { right.push(arr[i]); } } quick_sort(&mut left); quick_sort(&mut right); let mut i = 0; for _ in &left { arr[i] = left.pop().unwrap(); i += 1; } for _ in &right { arr[i] = right.pop().unwrap(); i += 1; } } `` 226 tokens generated (10.91 token/s) ```