Add a repeat penality to the llama2-c command line example. (#713)

* Add a repeat penality to the llama2-c command line example.

* Another fix attempt.

candle-examples/examples/llama2-c/main.rs

@@ -103,6 +103,14 @@ pub struct Args {
     /// Tokenizer config file.
     #[arg(long)]
     tokenizer: Option<String>,
+
+    /// Penalty to be applied for repeating tokens, 1. means no penalty.
+    #[arg(long, default_value_t = 1.1)]
+    repeat_penalty: f32,
+
+    /// The context size to consider for the repeat penalty.
+    #[arg(long, default_value_t = 64)]
+    repeat_last_n: usize,
 }
 
 impl Args {
@@ -268,6 +276,16 @@ fn run_inference(args: &InferenceCmd, common_args: &Args) -> Result<()> {
         let input = Tensor::new(ctxt, &device)?.unsqueeze(0)?;
         let logits = model.forward(&input, index_pos)?;
         let logits = logits.i((0, logits.dim(1)? - 1))?;
+        let logits = if common_args.repeat_penalty == 1. || tokens.is_empty() {
+            logits
+        } else {
+            let start_at = tokens.len().saturating_sub(common_args.repeat_last_n);
+            candle_transformers::utils::apply_repeat_penalty(
+                &logits,
+                common_args.repeat_penalty,
+                &tokens[start_at..],
+            )?
+        };
         index_pos += ctxt.len();
 
         let next_token = logits_processor.sample(&logits)?;