diff --git a/experimental/transformer/src/OPTGenerate.cc b/experimental/transformer/src/OPTGenerate.cc
index b94cb5fa..6b5a6a86 100644
--- a/experimental/transformer/src/OPTGenerate.cc
+++ b/experimental/transformer/src/OPTGenerate.cc
@@ -12,11 +12,10 @@ void OPT_sample_repetition_penalty(OPT_token_data_array * candidates, const int
             continue;
         }
 
-        // The academic publication that described this technique actually just only divided, but that would cause tokens with negative logits to become more likely, which is obviously wrong.
-        // This is common fix for this problem, which is to multiply by the penalty instead of dividing.
         if (candidates->data[i].logit <= 0) {
             candidates->data[i].logit *= penalty;
-        } else {
+        } 
+        else {
             candidates->data[i].logit /= penalty;
         }
     }
@@ -70,7 +69,6 @@ void OPT_sample_temperature(OPT_token_data_array * candidates_p, float temp) {
 //
 // sampling
 //
-
 void OPT_sample_softmax(OPT_token_data_array * candidates) {
     assert(candidates->size > 0);
 
@@ -122,7 +120,8 @@ void OPT_sample_top_k(OPT_token_data_array * candidates, int k, size_t min_keep)
         };
         if (k == (int) candidates->size) {
             std::sort(candidates->data, candidates->data + candidates->size, comp);
-        } else {
+        } 
+        else {
             std::partial_sort(candidates->data, candidates->data + k, candidates->data + candidates->size, comp);
         }
         candidates->sorted = true;
@@ -331,7 +330,6 @@ std::vector<int> OPTGenerate(std::vector<int> input_ids,
     std::vector<int> embd;
     std::vector<int> generate_ids;
 
-    //int n_past = 0;
     int n_consumed = 0;
     while ((int) input_ids.size() > n_consumed) {
         embd.push_back(input_ids[n_consumed]);
@@ -397,7 +395,6 @@ std::vector<int> OPTGenerate(std::vector<int> input_ids,
 
         int id = 0;
         if (temp <= 0) {
-            // Greedy sampling
             id = OPT_sample_token_greedy(&candidates_p);
         } 
         else {
@@ -422,15 +419,12 @@ std::vector<int> OPTGenerate(std::vector<int> input_ids,
                 id = OPT_sample_token(&candidates_p);
             }
         }
-        // printf("`%d`", candidates_p.size);
 
-        // add it to the context
         last_n_tokens.erase(last_n_tokens.begin());
         last_n_tokens.push_back(id);
         embd.push_back(id);
         generate_ids.push_back(id);
 
-        // decrement remaining sampling budget
         --n_remain;
     }