diff --git a/tokenizers/examples/train_bpe.rs b/tokenizers/examples/train_bpe.rs
index 4c12951b..f080b1ed 100644
--- a/tokenizers/examples/train_bpe.rs
+++ b/tokenizers/examples/train_bpe.rs
@@ -11,33 +11,36 @@ use std::path::Path;
 fn main() -> Result<()> {
     let vocab_size: usize = 100;
 
+    let min_frequency = 0;
+    let add_prefix_space = false;
+    let trim_offsets = false;
+    let use_regex = false;
+
     let mut trainer = BpeTrainerBuilder::new()
         .show_progress(true)
         .vocab_size(vocab_size)
-        .min_frequency(0)
+        .min_frequency(min_frequency)
         .special_tokens(vec![
-            AddedToken::from(String::from("<s>"), true),
-            AddedToken::from(String::from("<pad>"), true),
-            AddedToken::from(String::from("</s>"), true),
-            AddedToken::from(String::from("<unk>"), true),
-            AddedToken::from(String::from("<mask>"), true),
+            AddedToken::from(String::from("<PAD>"), true),
+            AddedToken::from(String::from("<MASK_TOKEN>"), true),
+            AddedToken::from(String::from("<BOS_TOKEN>"), true),
+            AddedToken::from(String::from("<EOS_TOKEN>"), true),
+            AddedToken::from(String::from("<UNK>"), true),
         ])
         .build();
 
     let mut tokenizer = TokenizerBuilder::new()
         .with_model(BPE::default())
-        .with_normalizer(Some(Sequence::new(vec![
-            Strip::new(true, true).into(),
-            NFC.into(),
-        ])))
-        .with_pre_tokenizer(Some(ByteLevel::default()))
-        .with_post_processor(Some(ByteLevel::default()))
-        .with_decoder(Some(ByteLevel::default()))
+        .with_normalizer(Some(Sequence::new(vec![])))
+        .with_pre_tokenizer(Some(ByteLevel::new(add_prefix_space, trim_offsets, use_regex)))
+        .with_post_processor(Some(ByteLevel::new(add_prefix_space, trim_offsets, use_regex)))
+        .with_decoder(Some(ByteLevel::new(add_prefix_space, trim_offsets, use_regex)))
         .build()?;
 
     let pretty = false;
     tokenizer
         .train_from_pretokenized_data(
+            // .train_from_files(
             &mut trainer,
             vec!["/home/felipe_cohere_com/pretokenized.tsv".to_string()],
         )?
diff --git a/tokenizers/src/models/bpe/trainer.rs b/tokenizers/src/models/bpe/trainer.rs
index b53070ac..8fb81862 100644
--- a/tokenizers/src/models/bpe/trainer.rs
+++ b/tokenizers/src/models/bpe/trainer.rs
@@ -683,16 +683,19 @@ impl Trainer for BpeTrainer {
             .maybe_par_bridge()
             .map(|sequence| {
                 let split_seq = process(sequence.as_ref())?;
+                let mut count_str = split_seq.last().expect("This should work").to_string();
                 let segment = split_seq[0]
                     .replace("<TSV_ESCAPE_N>", "\n")
                     .replace("<TSV_ESCAPE_T>", "\t")
                     .replace("<TSV_ESCAPE_R>", "\r")
                     .clone();
 
-                let mut count_str = split_seq[1].to_string();
+                
                 let count_int: u64 = count_str.trim_end().parse().unwrap();
                 let mut map = HashMap::new();
-                map.insert(segment, count_int);
+                for i in 0..split_seq.len() - 1 {
+                    map.insert(split_seq[i].clone(), count_int);
+                }                
                 Ok(map)
             })
             .reduce(
diff --git a/tokenizers/src/models/unigram/trainer.rs b/tokenizers/src/models/unigram/trainer.rs
index d83b507a..065edffb 100644
--- a/tokenizers/src/models/unigram/trainer.rs
+++ b/tokenizers/src/models/unigram/trainer.rs
@@ -666,14 +666,19 @@ impl Trainer for UnigramTrainer {
             .maybe_par_bridge()
             .map(|sequence| {
                 let split_seq = process(sequence.as_ref())?;
+                let mut count_str = split_seq.last().expect("This should work").to_string();
                 let segment = split_seq[0]
                     .replace("<TSV_ESCAPE_N>", "\n")
                     .replace("<TSV_ESCAPE_T>", "\t")
                     .replace("<TSV_ESCAPE_R>", "\r")
-                    .clone();                let mut count_str = split_seq[1].to_string();
+                    .clone();
+
+                
                 let count_int: u32 = count_str.trim_end().parse().unwrap();
                 let mut map = HashMap::new();
-                map.insert(segment, count_int);
+                for i in 0..split_seq.len() - 1 {
+                    map.insert(split_seq[i].clone(), count_int);
+                }                
                 Ok(map)
             })
             .reduce(
diff --git a/tokenizers/src/models/wordlevel/trainer.rs b/tokenizers/src/models/wordlevel/trainer.rs
index 21ee1edf..52ed0f2d 100644
--- a/tokenizers/src/models/wordlevel/trainer.rs
+++ b/tokenizers/src/models/wordlevel/trainer.rs
@@ -135,14 +135,19 @@ impl Trainer for WordLevelTrainer {
             .maybe_par_bridge()
             .map(|sequence| {
                 let split_seq = process(sequence.as_ref())?;
+                let mut count_str = split_seq.last().expect("This should work").to_string();
                 let segment = split_seq[0]
                     .replace("<TSV_ESCAPE_N>", "\n")
                     .replace("<TSV_ESCAPE_T>", "\t")
                     .replace("<TSV_ESCAPE_R>", "\r")
-                    .clone();                  let mut count_str = split_seq[1].to_string();
+                    .clone();
+
+                
                 let count_int: u64 = count_str.trim_end().parse().unwrap();
                 let mut map = HashMap::new();
-                map.insert(segment, count_int);
+                for i in 0..split_seq.len() - 1 {
+                    map.insert(split_seq[i].clone(), count_int);
+                }                
                 Ok(map)
             })
             .reduce(
diff --git a/tokenizers/src/tokenizer/mod.rs b/tokenizers/src/tokenizer/mod.rs
index 61ea10fa..a9041422 100644
--- a/tokenizers/src/tokenizer/mod.rs
+++ b/tokenizers/src/tokenizer/mod.rs
@@ -1198,7 +1198,15 @@ where
                     }),
                     |seq| {
                         let split_seq: Vec<String> = seq.split('\t').map(|s| s.to_string()).collect();
-                        Ok(split_seq)
+                        let normalized = self.do_normalize(split_seq[0].clone())?;
+                        let pre_tokenized = self.do_pre_tokenize(normalized)?;
+                        let mut pretokenized_and_freq: Vec<_> = pre_tokenized
+                                .get_splits(OffsetReferential::Original, OffsetType::Byte)
+                                .into_iter()
+                                .map(|(s, _, _)| s.to_owned())
+                                .collect();
+                        pretokenized_and_freq.extend(vec![split_seq[1].clone()].iter().map(|s| s.to_string()));
+                        Ok(pretokenized_and_freq)
                     },
                 )?;