diff --git a/candle-examples/examples/quantized/main.rs b/candle-examples/examples/quantized/main.rs
index 2dc46217..e4a7a360 100644
--- a/candle-examples/examples/quantized/main.rs
+++ b/candle-examples/examples/quantized/main.rs
@@ -325,6 +325,14 @@ struct Args {
     /// Display the token for the specified prompt.
     #[arg(long)]
     verbose_prompt: bool,
+
+    /// Penalty to be applied for repeating tokens, 1. means no penalty.
+    #[arg(long, default_value_t = 1.0)]
+    repeat_penalty: f32,
+
+    /// The context size to consider for the repeat penalty.
+    #[arg(long, default_value_t = 64)]
+    repeat_last_n: usize,
 }
 
 impl Args {
@@ -378,6 +386,22 @@ fn print_token(next_token: u32, tokenizer: &Tokenizer) {
     }
 }
 
+fn apply_repeat_penalty(logits: &Tensor, penalty: f32, context: &[u32]) -> Result<Tensor> {
+    let mut logits = logits.to_vec1::<f32>()?;
+    let context: std::collections::HashSet<_> = context.iter().collect();
+    for (token_id, logit) in logits.iter_mut().enumerate() {
+        if context.contains(&(token_id as u32)) {
+            if *logit >= 0. {
+                *logit /= penalty
+            } else {
+                *logit *= penalty
+            }
+        }
+    }
+    let logits_len = logits.len();
+    Tensor::from_vec(logits, logits_len, &Device::Cpu)
+}
+
 fn main() -> anyhow::Result<()> {
     use tracing_chrome::ChromeLayerBuilder;
     use tracing_subscriber::prelude::*;
@@ -439,6 +463,7 @@ fn main() -> anyhow::Result<()> {
     }
 
     let prompt_tokens = tokens.get_ids().to_vec();
+    let mut all_tokens = vec![];
     let mut logits_processor = LogitsProcessor::new(args.seed, args.temperature);
 
     print!("{prompt}");
@@ -451,6 +476,7 @@ fn main() -> anyhow::Result<()> {
         logits_processor.sample(&logits)?
     };
     let prompt_dt = start_prompt_processing.elapsed();
+    all_tokens.push(next_token);
     print_token(next_token, &tokenizer);
 
     let to_sample = args.sample_len.saturating_sub(1);
@@ -459,7 +485,14 @@ fn main() -> anyhow::Result<()> {
         let input = Tensor::new(&[next_token], &Device::Cpu)?.unsqueeze(0)?;
         let logits = model.forward(&input, prompt_tokens.len() + index)?;
         let logits = logits.squeeze(0)?;
+        let logits = if args.repeat_penalty == 1. {
+            logits
+        } else {
+            let start_at = all_tokens.len().saturating_sub(args.repeat_last_n);
+            apply_repeat_penalty(&logits, args.repeat_penalty, &all_tokens[start_at..])?
+        };
         next_token = logits_processor.sample(&logits)?;
+        all_tokens.push(next_token);
         print_token(next_token, &tokenizer);
     }
     let dt = start_post_prompt.elapsed();