diff --git a/bindings/python/src/trainers.rs b/bindings/python/src/trainers.rs
index 1c1c9310a..707dc7230 100644
--- a/bindings/python/src/trainers.rs
+++ b/bindings/python/src/trainers.rs
@@ -183,12 +183,12 @@ impl PyBpeTrainer {
     }
 
     #[getter]
-    fn get_min_frequency(self_: PyRef<Self>) -> u32 {
+    fn get_min_frequency(self_: PyRef<Self>) -> u64 {
         getter!(self_, BpeTrainer, min_frequency)
     }
 
     #[setter]
-    fn set_min_frequency(self_: PyRef<Self>, freq: u32) {
+    fn set_min_frequency(self_: PyRef<Self>, freq: u64) {
         setter!(self_, BpeTrainer, min_frequency, freq);
     }
 
@@ -397,12 +397,12 @@ impl PyWordPieceTrainer {
     }
 
     #[getter]
-    fn get_min_frequency(self_: PyRef<Self>) -> u32 {
+    fn get_min_frequency(self_: PyRef<Self>) -> u64 {
         getter!(self_, WordPieceTrainer, min_frequency())
     }
 
     #[setter]
-    fn set_min_frequency(self_: PyRef<Self>, freq: u32) {
+    fn set_min_frequency(self_: PyRef<Self>, freq: u64) {
         setter!(self_, WordPieceTrainer, @set_min_frequency, freq);
     }
 
@@ -589,12 +589,12 @@ impl PyWordLevelTrainer {
     }
 
     #[getter]
-    fn get_min_frequency(self_: PyRef<Self>) -> u32 {
+    fn get_min_frequency(self_: PyRef<Self>) -> u64 {
         getter!(self_, WordLevelTrainer, min_frequency)
     }
 
     #[setter]
-    fn set_min_frequency(self_: PyRef<Self>, freq: u32) {
+    fn set_min_frequency(self_: PyRef<Self>, freq: u64) {
         setter!(self_, WordLevelTrainer, min_frequency, freq);
     }
 
diff --git a/tokenizers/src/models/bpe/trainer.rs b/tokenizers/src/models/bpe/trainer.rs
index 3821cdab4..303fdbc81 100644
--- a/tokenizers/src/models/bpe/trainer.rs
+++ b/tokenizers/src/models/bpe/trainer.rs
@@ -11,7 +11,7 @@ use std::collections::{BinaryHeap, HashMap, HashSet};
 #[derive(Debug, Eq)]
 struct Merge {
     pair: Pair,
-    count: u32,
+    count: u64,
     pos: HashSet<usize>,
 }
 impl PartialEq for Merge {
@@ -36,7 +36,7 @@ impl Ord for Merge {
 }
 
 struct Config {
-    min_frequency: u32,
+    min_frequency: u64,
     vocab_size: usize,
     show_progress: bool,
     special_tokens: Vec<AddedToken>,
@@ -79,7 +79,7 @@ impl BpeTrainerBuilder {
 
     /// Set the expected minimum frequency
     #[must_use]
-    pub fn min_frequency(mut self, frequency: u32) -> Self {
+    pub fn min_frequency(mut self, frequency: u64) -> Self {
         self.config.min_frequency = frequency;
         self
     }
@@ -176,7 +176,7 @@ impl BpeTrainerBuilder {
 #[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq)]
 pub struct BpeTrainer {
     /// The minimum frequency a pair must have to produce a merge operation
-    pub min_frequency: u32,
+    pub min_frequency: u64,
     /// The target vocabulary size
     pub vocab_size: usize,
     /// Whether to show progress while training
@@ -195,7 +195,7 @@ pub struct BpeTrainer {
     /// An optional parameter to limit the max length of any single token
     pub max_token_length: Option<usize>,
 
-    words: HashMap<String, u32>,
+    words: HashMap<String, u64>,
 }
 
 impl Default for BpeTrainer {
@@ -205,7 +205,7 @@ impl Default for BpeTrainer {
 }
 
 impl BpeTrainer {
-    pub fn new(min_frequency: u32, vocab_size: usize) -> Self {
+    pub fn new(min_frequency: u64, vocab_size: usize) -> Self {
         Self {
             min_frequency,
             vocab_size,
@@ -263,7 +263,7 @@ impl BpeTrainer {
     /// Compute the initial alphabet and limit it if relevant
     fn compute_alphabet(
         &self,
-        wc: &HashMap<String, u32>,
+        wc: &HashMap<String, u64>,
         w2id: &mut HashMap<String, u32>,
         id2w: &mut Vec<String>,
     ) {
@@ -322,13 +322,13 @@ impl BpeTrainer {
     /// Tokenize words and add subwords to the vocabulary when relevant
     fn tokenize_words(
         &self,
-        wc: &HashMap<String, u32>,
+        wc: &HashMap<String, u64>,
         w2id: &mut HashMap<String, u32>,
         id2w: &mut Vec<String>,
         p: &Option<ProgressBar>,
-    ) -> (Vec<Word>, Vec<u32>) {
+    ) -> (Vec<Word>, Vec<u64>) {
         let mut words: Vec<Word> = Vec::with_capacity(wc.len());
-        let mut counts: Vec<u32> = Vec::with_capacity(wc.len());
+        let mut counts: Vec<u64> = Vec::with_capacity(wc.len());
 
         for (word, count) in wc {
             let mut current_word = Word::new();
@@ -373,7 +373,7 @@ impl BpeTrainer {
     fn count_pairs(
         &self,
         words: &[Word],
-        counts: &[u32],
+        counts: &[u64],
         p: &Option<ProgressBar>,
     ) -> (HashMap<Pair, i32>, HashMap<Pair, HashSet<usize>>) {
         words
@@ -431,7 +431,7 @@ impl BpeTrainer {
 
     pub fn do_train(
         &self,
-        word_counts: &HashMap<String, u32>,
+        word_counts: &HashMap<String, u64>,
         model: &mut BPE,
     ) -> Result<Vec<AddedToken>> {
         let mut word_to_id: HashMap<String, u32> = HashMap::with_capacity(self.vocab_size);
@@ -470,7 +470,7 @@ impl BpeTrainer {
             if count > 0 {
                 queue.push(Merge {
                     pair,
-                    count: count as u32,
+                    count: count as u64,
                     pos,
                 });
             }
@@ -493,8 +493,8 @@ impl BpeTrainer {
             }
 
             let mut top = queue.pop().unwrap();
-            if top.count != pair_counts[&top.pair] as u32 {
-                top.count = pair_counts[&top.pair] as u32;
+            if top.count != pair_counts[&top.pair] as u64 {
+                top.count = pair_counts[&top.pair] as u64;
                 queue.push(top);
                 continue;
             }
@@ -573,7 +573,7 @@ impl BpeTrainer {
                 if count > 0 {
                     queue.push(Merge {
                         pair,
-                        count: count as u32,
+                        count: count as u64,
                         pos,
                     });
                 }
@@ -632,7 +632,7 @@ impl Trainer for BpeTrainer {
         S: AsRef<str> + Send,
         F: Fn(&str) -> Result<Vec<String>> + Sync,
     {
-        let words: Result<HashMap<String, u32>> = iterator
+        let words: Result<HashMap<String, u64>> = iterator
             .maybe_par_bridge()
             .map(|sequence| {
                 let words = process(sequence.as_ref())?;
@@ -665,7 +665,7 @@ mod tests {
 
     #[test]
     fn test_train() {
-        let word_counts: HashMap<String, u32> = [
+        let word_counts: HashMap<String, u64> = [
             ("roses".into(), 1),
             ("are".into(), 2),
             ("red".into(), 1),
@@ -744,7 +744,7 @@ mod tests {
          */
 
         let max_token_length = 16;
-        let long_word_counts: HashMap<String, u32> = [
+        let long_word_counts: HashMap<String, u64> = [
             ("singlelongtokenwithoutcasechange", 2),
             ("singleLongTokenWithCamelCaseChange", 2),
             ("Longsingletokenwithpunctu@t!onwithin", 2),
@@ -784,7 +784,7 @@ mod tests {
         // directly compares tokens with known expected values.
         // maybe unstable depending on specific settings or changes.
          */
-        let long_word_counts: HashMap<String, u32> = [
+        let long_word_counts: HashMap<String, u64> = [
             ("sin", 2),
             ("Sin", 2),
             ("Lon", 2),
diff --git a/tokenizers/src/models/wordlevel/trainer.rs b/tokenizers/src/models/wordlevel/trainer.rs
index d4048b15d..c52ad08d7 100644
--- a/tokenizers/src/models/wordlevel/trainer.rs
+++ b/tokenizers/src/models/wordlevel/trainer.rs
@@ -10,7 +10,7 @@ use std::collections::HashMap;
 pub struct WordLevelTrainer {
     /// The minimum frequency a word must have to be part of the vocabulary
     #[builder(default = "0")]
-    pub min_frequency: u32,
+    pub min_frequency: u64,
     /// The target vocabulary size
     #[builder(default = "30_000")]
     pub vocab_size: usize,
@@ -22,7 +22,7 @@ pub struct WordLevelTrainer {
     pub special_tokens: Vec<AddedToken>,
 
     #[builder(default, private)]
-    words: HashMap<String, u32>,
+    words: HashMap<String, u64>,
 }
 
 impl Default for WordLevelTrainer {
@@ -38,14 +38,14 @@ impl WordLevelTrainer {
 
     fn do_train(
         &self,
-        word_counts: &HashMap<String, u32>,
+        word_counts: &HashMap<String, u64>,
         model: &mut WordLevel,
     ) -> Result<Vec<AddedToken>> {
         let mut ordered_counts = word_counts.iter().collect::<Vec<_>>();
 
         //sort the word counts first by inverse counts and then by word, in order
         //to keep the sorting deterministic in case of equal counts
-        let cmp = |l: &(&String, &u32), r: &(&String, &u32)| -> Ordering {
+        let cmp = |l: &(&String, &u64), r: &(&String, &u64)| -> Ordering {
             let count_comp: Ordering = l.1.cmp(r.1);
             if count_comp != Ordering::Equal {
                 return count_comp.reverse();
@@ -100,7 +100,7 @@ impl Trainer for WordLevelTrainer {
         S: AsRef<str> + Send,
         F: Fn(&str) -> Result<Vec<String>> + Sync,
     {
-        let words: Result<HashMap<String, u32>> = iterator
+        let words: Result<HashMap<String, u64>> = iterator
             .maybe_par_bridge()
             .map(|sequence| {
                 let words = process(sequence.as_ref())?;
@@ -132,7 +132,7 @@ mod tests {
 
     #[test]
     fn test_train() {
-        let word_counts: HashMap<String, u32> = [
+        let word_counts: HashMap<String, u64> = [
             ("the".into(), 25),
             ("roses".into(), 22),
             ("are".into(), 24),
diff --git a/tokenizers/src/models/wordpiece/trainer.rs b/tokenizers/src/models/wordpiece/trainer.rs
index 1adcc2be4..58a5abc8f 100644
--- a/tokenizers/src/models/wordpiece/trainer.rs
+++ b/tokenizers/src/models/wordpiece/trainer.rs
@@ -26,7 +26,7 @@ impl WordPieceTrainerBuilder {
 
     /// Set the expected minimum frequency
     #[must_use]
-    pub fn min_frequency(mut self, frequency: u32) -> Self {
+    pub fn min_frequency(mut self, frequency: u64) -> Self {
         self.bpe_trainer_builder = self.bpe_trainer_builder.min_frequency(frequency);
         self
     }
@@ -94,11 +94,11 @@ pub struct WordPieceTrainer {
 }
 
 impl WordPieceTrainer {
-    pub fn min_frequency(&self) -> u32 {
+    pub fn min_frequency(&self) -> u64 {
         self.bpe_trainer.min_frequency
     }
 
-    pub fn set_min_frequency(&mut self, freq: u32) {
+    pub fn set_min_frequency(&mut self, freq: u64) {
         self.bpe_trainer.min_frequency = freq;
     }