llama : Added support for Viking pre-tokenizer (#8577)

Author: m18coppola

convert_hf_to_gguf.py

@@ -593,6 +593,9 @@ def get_vocab_base_pre(self, tokenizer) -> str:
         if chkhsh == "b53802fb28e26d645c3a310b34bfe07da813026ec7c7716883404d5e0f8b1901":
             # ref: https://huggingface.co/core42/jais-13b
             res = "jais"
+        if chkhsh == "aa78fe8b04bc622b077520b1fb3d3a5c6f7a53dd375e2361e62599be3cf58de1":
+            # ref: https://huggingface.co/mistralai/Mistral-Nemo-Base-2407
+            res = "tekken"
 
         if res is None:
             logger.warning("\n")

convert_hf_to_gguf_update.py

@@ -91,6 +91,7 @@ class TOKENIZER_TYPE(IntEnum):
     {"name": "gemma-2",        "tokt": TOKENIZER_TYPE.SPM, "repo": "https://huggingface.co/google/gemma-2-9b", },
     {"name": "jais",           "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/core42/jais-13b", },
     {"name": "t5",             "tokt": TOKENIZER_TYPE.UGM, "repo": "https://huggingface.co/google-t5/t5-small", },
+    {"name": "tekken",         "tokt": TOKENIZER_TYPE.BPE, "repo": "https://huggingface.co/mistralai/Mistral-Nemo-Base-2407", },
 ]
 
 

include/llama.h

@@ -92,6 +92,7 @@ extern "C" {
         LLAMA_VOCAB_PRE_TYPE_CHATGLM4       = 17,
         LLAMA_VOCAB_PRE_TYPE_VIKING         = 18,
         LLAMA_VOCAB_PRE_TYPE_JAIS           = 19,
+        LLAMA_VOCAB_PRE_TYPE_TEKKEN         = 20,
     };
 
     // note: these values should be synchronized with ggml_rope

src/llama.cpp

@@ -5517,6 +5517,12 @@ static void llm_load_vocab(
                 tokenizer_pre == "viking") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_VIKING;
                 vocab.tokenizer_clean_spaces = false;
+            } else if (
+                tokenizer_pre == "tekken") {
+                vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_TEKKEN;
+                vocab.tokenizer_clean_spaces = true;
+                vocab.tokenizer_ignore_merges = true;
+                vocab.tokenizer_add_bos = true;
             } else if (
                 tokenizer_pre == "jais") {
                 vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
@@ -15581,6 +15587,13 @@ struct llm_tokenizer_bpe {
                     "\\p{N}",
                 };
                 break;
+            case LLAMA_VOCAB_PRE_TYPE_TEKKEN:
+                    // original regex from tokenizer.json
+                    // "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+|[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
+                regex_exprs = {
+                    "[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))*((?=[\\p{L}])([^A-Z]))+|[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))+((?=[\\p{L}])([^A-Z]))*|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+                };
+                break;
             default:
                 // default regex for BPE tokenization pre-processing
                 regex_exprs = {