diff --git a/src/tokenizers.js b/src/tokenizers.js
index 57ab21fa8..1d92bc074 100644
--- a/src/tokenizers.js
+++ b/src/tokenizers.js
@@ -3488,6 +3488,10 @@ export class M2M100Tokenizer extends PreTrainedTokenizer {
 export class WhisperTokenizer extends PreTrainedTokenizer {
     _default_chat_template = `{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}`;
 
+    get timestamp_begin() {
+        return this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0] + 1;
+    }
+
     /**
      * Decodes automatic speech recognition (ASR) sequences.
      * @param {Array<{tokens: bigint[], token_timestamps?: number[], stride: number[]}>} sequences The sequences to decode.
@@ -3534,7 +3538,7 @@ export class WhisperTokenizer extends PreTrainedTokenizer {
         const chunks = [];
         let chunk = new_chunk();
         let time_offset = 0.0;
-        const timestamp_begin = this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0] + 1;
+        const timestamp_begin = this.timestamp_begin;
 
         let previous_tokens = [];
         let previous_token_timestamps = [];
@@ -3572,11 +3576,11 @@ export class WhisperTokenizer extends PreTrainedTokenizer {
 
                 if (stride_right) {
                     for (let i = token_ids.length - 1; i >= 0; --i) {
-                        const token = token_ids[i];
+                        const token = Number(token_ids[i]);
                         if (token >= timestamp_begin) {
                             // There can be several token in the right stride
                             // But the last one is ALWAYS going to be skipped
-                            if (last_timestamp !== null && (Number(token) - timestamp_begin) * time_precision < right_stride_start) {
+                            if (last_timestamp !== null && (token - timestamp_begin) * time_precision < right_stride_start) {
                                 break;
                             }
                             last_timestamp = token;
@@ -3924,7 +3928,7 @@ export class WhisperTokenizer extends PreTrainedTokenizer {
     ) {
         let text;
         // @ts-ignore
-        if (decode_args && decode_args.decode_with_timestamps) {
+        if (decode_args?.decode_with_timestamps) {
             if (token_ids instanceof Tensor) {
                 token_ids = prepareTensorForDecode(token_ids);
             }
@@ -3950,9 +3954,10 @@ export class WhisperTokenizer extends PreTrainedTokenizer {
         const timestamp_begin = Array.from(this.all_special_ids).at(-1) + 1;
         /**@type {Array} */
         let outputs = [[]];
-        for (const token of token_ids) {
+        for (let token of token_ids) {
+            token = Number(token);
             if (token >= timestamp_begin) {
-                const timestamp = round((Number(token) - timestamp_begin) * time_precision, 2);
+                const timestamp = ((token - timestamp_begin) * time_precision).toFixed(2);
                 outputs.push(`<|${timestamp}|>`);
                 outputs.push([]);
             } else {
@@ -3960,13 +3965,7 @@ export class WhisperTokenizer extends PreTrainedTokenizer {
             }
         }
         outputs = outputs.map(
-            s => {
-                if (typeof s === 'string') {
-                    return s;
-                } else {
-                    return super.decode(s, decode_args);
-                }
-            }
+            s => typeof s === 'string' ? s : super.decode(s, decode_args)
         )
 
         return outputs.join('');