diff --git a/src/llama-sampling.cpp b/src/llama-sampling.cpp
index 9938f0f3d..9826bdd09 100644
--- a/src/llama-sampling.cpp
+++ b/src/llama-sampling.cpp
@@ -1657,7 +1657,6 @@ struct llama_sampler_top_n_sigma {
 static const char * llama_sampler_top_n_sigma_name(const struct llama_sampler * /*smpl*/) {
     return "top-n-sigma";
 }
-#include <iostream>
 
 static void llama_sampler_top_n_sigma_apply(struct llama_sampler * smpl, llama_token_data_array * cur_p) {
     const auto * ctx = (llama_sampler_top_n_sigma *) smpl->ctx;
@@ -1671,18 +1670,18 @@ static void llama_sampler_top_n_sigma_apply(struct llama_sampler * smpl, llama_t
         }
         logits_sum += cur_p->data[i].logit;
     }
-    float mean = (float)logits_sum/cur_p->size;
+    float mean = logits_sum/cur_p->size;
 
     // calculate standard deviation
     float acc = 0;
     for(size_t i = 0; i < cur_p->size; ++i){
         acc += pow(cur_p->data[i].logit - mean, 2);
     }
-    float std = sqrt((float)acc/cur_p->size);
+    float std = sqrt(acc/cur_p->size);
 
     //apply mask
     for(size_t i = 0; i < cur_p->size; ++i){
-        if(cur_p->data[i].logit < max - ((float)ctx->n * std)) {
+        if(cur_p->data[i].logit < max - ctx->n * std) {
             cur_p->data[i].logit = -INFINITY;
         }
     }