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README.md

@@ -1,7 +1,8 @@
 ---
 license: mit
 language:
-- dan  # ISO 639-3 code or "und" if not identifiable
+- cmn #
+- jpn #['cmn_Hani', 'jpn_Jpan']  # ISO 639-3 code or "und" if not identifiable
 tags:
 - tokenizer
 - bpe
@@ -9,31 +10,31 @@ tags:
 - fineweb2
 ---
 
-# Byte-Level BPE Tokenizer: dan_Latn (16K)
+# Byte-Level BPE Tokenizer: ['cmn_Hani', 'jpn_Jpan'] (16K)
 
-A **Byte-Level BPE** tokenizer trained on **dan_Latn** data from Fineweb-2-HQ.
+A **Byte-Level BPE** tokenizer trained on **['cmn_Hani', 'jpn_Jpan']** data from Fineweb-2-HQ.
 
 ## Training Details
 
 | Parameter | Value |
 |-----------|-------|
 | Algorithm | Byte-Level BPE |
-| Language | `dan_Latn` |
+| Language | `['cmn_Hani', 'jpn_Jpan']` |
 | Target Vocab Size | 16,000 |
-| Final Vocab Size | 16,961 |
-| Pre-tokenizer | custom:dan_Latn |
+| Final Vocab Size | 17,900 |
+| Pre-tokenizer | custom:jpn_Jpan |
 | Number handling | ltr_3digit |
 | Contraction handling | True |
 | Normalizer | NFC |
 | Special Tokens | `<s>`, `</s>`, `<pad>`, `<unk>` |
-| Training Shards | 2 |
+| Training Shards | 4 |
 
 ## Usage
 
 ```python
 from transformers import AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("flexitok/bpe_script_Germ_16000")
+tokenizer = AutoTokenizer.from_pretrained("flexitok/bpe_script_CmJp_16000")
 tokens = tokenizer.encode("Hello, world!")
 ```
 
@@ -46,4 +47,4 @@ tokens = tokenizer.encode("Hello, world!")
 ## Sample Encoding
 | Text | Tokens | Token IDs |
 |------|--------|-----------|
-| `Hello, world! 12345 This is a test. こんにちは` | `H, ello, ,, Ġw, orld, !, Ġ, 123, 45, ĠTh, is, Ġis, Ġa, Ġtest, ., Ġ, ãģ, ĵ, ã, Ĥ` | `42, 12891, 14, 819, 4384, 3, 223, 16661, 3909, 1897, 317, 998, 263, 1922, 16, 223, 7445, 244, 162, 227` |
+| `Hello, world! 12345 This is a test. こんにちは` | `H, ell, o, ,, Ġw, orld, !, Ġ, 123, 45, ĠTh, is, Ġis, Ġa, Ġt, est, ., Ġ, ãģ, ĵ` | `42, 3452, 81, 14, 2927, 10693, 3, 223, 12071, 3557, 9838, 1476, 6231, 3791, 4071, 3540, 16, 223, 3577, 244` |