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-tutorial/src
    
    the code of the file until where you have to start completion: use anyhow::{anyhow, Error as E, Result};
use candle_core::{Device, IndexOp, Tensor};
use candle_nn::VarBuilder;
use hf_hub::{api::sync::Api, Cache, Repo, RepoType};
use tokenizers::Tokenizer;

use candle_tutorial::models::roberta::{RobertaConfig, RobertaModel, FLOATING_DTYPE};

fn build_model_and_tokenizer() -> Result<(RobertaModel, Tokenizer)> {
    let device
    
fn build_model_and_tokenizer() -> Result<(RobertaModel, Tokenizer)> {
    let device = Device::Cpu;
    let default_model = "roberta-base".to_string();
    let default_revision = "main".to_string();
    let (model_id, revision) = (default_model, default_revision);
    let repo = Repo::with_revision(model_id, RepoType::Model, revision);
    let offline = false;

    let (config_filename, tokenizer_filename, weights_filename) = if offline {
        let cache = Cache::default().repo(repo);
        (
            cache
                .get("config.json")
                .ok_or(anyhow!("Missing config file in cache"))?,
            cache
                .get("tokenizer.json")
                .ok_or(anyhow!("Missing tokenizer file in cache"))?,
            cache
                .get("model.safetensors")
                .ok_or(anyhow!("Missing weights file in cache"))?,
        )
    } else {
        let api = Api::new()?;
        let api = api.repo(repo);
        (
            api.get("config.json")?,
            api.get("tokenizer.json")?,
            api.get("model.safetensors")?,
        )
    };

    println!("config_filename: {}", config_filename.display());

    let config = std::fs::read_to_string(config_filename)?;
    let config: RobertaConfig = serde_json::from_str(&config)?;
    let tokenizer = Tokenizer::from_file(tokenizer_filename).map_err(E::msg)?;

    let vb = unsafe {
        VarBuilder::from_mmaped_safetensors(&[weights_filename], FLOATING_DTYPE, &device)?
    };
    let model = RobertaModel::load(vb, &config)?;
    Ok((model, tokenizer))
}