You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: main.rs
    path of file: ./repos/candle/candle-examples/examples/replit-code
    
    the code of the file until where you have to start completion: #[cfg(feature = "mkl")]
extern crate intel_mkl_src;

#[cfg(feature = "accelerate")]
extern crate accelerate_src;

use anyhow::{Error as E, Result};
use clap::Parser;

use candle_transformers::models::mpt::{Config, Model as M};
use candle_transformers::models::quantized_mpt::Model as Q;

use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::generation::LogitsProcessor;
use hf_hub::{api::sync::Api, Repo, RepoType};
use tokenizers::Tokenizer;

enum Model {
    M(M),
    Q(Q),
}

impl Model {
    fn forward(&mut self, xs: &Tensor) -> candle::Result<Tensor> {
        match self {
            Self::M(model) => model.forward(xs),
            Self::Q(model) => model.forward(xs),
        }
    }
}

struct TextGeneration {
    model: Model,
    device: Device,
    tokenizer: Tokenizer,
    logits_processor: LogitsProcessor,
    repeat_penalty: f32,
    repeat_last_n: usize,
    verbose_prompt: bool,
}

impl TextGeneration {
    #[allow(clippy::too_many_arguments)]
    fn new(
        model: Model,
        tokenizer: Tokenizer,
        seed: u64,
        temp: Option<f64>,
        top_p: Option<f64>,
        repeat_penalty: f32,
        repeat_last_n: usize,
        verbose_prompt: bool,
        device: &Device,
    ) -> Self {
        let logits_processor = LogitsProcessor::new(seed, temp, top_p);
    
    
fn main() -> Result<()> {
    use tracing_chrome::ChromeLayerBuilder;
    use tracing_subscriber::prelude::*;

    let args = Args::parse();
    let _guard = if args.tracing {
        let (chrome_layer, guard) = ChromeLayerBuilder::new().build();
        tracing_subscriber::registry().with(chrome_layer).init();
        Some(guard)
    } else {
        None
    };
    println!(
        "avx: {}, neon: {}, simd128: {}, f16c: {}",
        candle::utils::with_avx(),
        candle::utils::with_neon(),
        candle::utils::with_simd128(),
        candle::utils::with_f16c()
    );
    println!(
        "temp: {:.2} repeat-penalty: {:.2} repeat-last-n: {}",
        args.temperature.unwrap_or(0.),
        args.repeat_penalty,
        args.repeat_last_n
    );

    let start = std::time::Instant::now();
    let api = Api::new()?;
    let model_id = match args.model_id {
        Some(model_id) => model_id.to_string(),
        None => "lmz/candle-replit-code".to_string(),
    };
    let revision = match args.revision {
        Some(rev) => rev.to_string(),
        None => "main".to_string(),
    };
    let repo = api.repo(Repo::with_revision(model_id, RepoType::Model, revision));
    let tokenizer_filename = match args.tokenizer {
        Some(file) => std::path::PathBuf::from(file),
        None => repo.get("tokenizer.json")?,
    };
    let filename = match args.weight_file {
        Some(weight_file) => std::path::PathBuf::from(weight_file),
        None => {
            if args.quantized {
                repo.get("model-replit-code-v1_5-q4k.gguf")?
            } else {
                repo.get("model.safetensors")?
            }
        }
    };
    println!("retrieved the files in {:?}", start.elapsed());
    let tokenizer = Tokenizer::from_file(tokenizer_filename).map_err(E::msg)?;

    let start = std::time::Instant::now();
    let device = candle_examples::device(args.cpu)?;
    let config = Config::replit_code_v1_5_3b();
    let model = if args.quantized {
        let vb =
            candle_transformers::quantized_var_builder::VarBuilder::from_gguf(&filename, &device)?;
        Model::Q(Q::new(&config, vb.pp("transformer"))?)
    } else {
        let vb = unsafe { VarBuilder::from_mmaped_safetensors(&[filename], DType::F32, &device)? };
        Model::M(M::new(&config, vb.pp("transformer"))?)
    };
    println!("loaded the model in {:?}", start.elapsed());

    let mut pipeline = TextGeneration::new(
        model,
        tokenizer,
        args.seed,
        args.temperature,
        args.top_p,
        args.repeat_penalty,
        args.repeat_last_n,
        args.verbose_prompt,
        &device,
    );
    pipeline.run(&args.prompt, args.sample_len)?;
    Ok(())
}