Merge pull request #2873 from SillyTavern/nemo-tokenizer

Add Mistral Nemo downloadable tokenizer

public/index.html

@@ -3339,7 +3339,8 @@
                                     <option value="16">Command-R</option>
                                     <option value="4">NerdStash (NovelAI Clio)</option>
                                     <option value="5">NerdStash v2 (NovelAI Kayra)</option>
-                                    <option value="7">Mistral</option>
+                                    <option value="7">Mistral V1</option>
+                                    <option value="17">Mistral Nemo</option>
                                     <option value="8">Yi</option>
                                     <option value="11">Claude 1/2</option>
                                     <option value="6">API (WebUI / koboldcpp)</option>

public/scripts/tokenizers.js

@@ -30,6 +30,7 @@ export const tokenizers = {
     JAMBA: 14,
     QWEN2: 15,
     COMMAND_R: 16,
+    NEMO: 17,
     BEST_MATCH: 99,
 };
 
@@ -43,6 +44,7 @@ export const ENCODE_TOKENIZERS = [
     tokenizers.JAMBA,
     tokenizers.QWEN2,
     tokenizers.COMMAND_R,
+    tokenizers.NEMO,
     // uncomment when NovelAI releases Kayra and Clio weights, lol
     //tokenizers.NERD,
     //tokenizers.NERD2,
@@ -121,6 +123,11 @@ const TOKENIZER_URLS = {
         decode: '/api/tokenizers/command-r/decode',
         count: '/api/tokenizers/command-r/encode',
     },
+    [tokenizers.NEMO]: {
+        encode: '/api/tokenizers/nemo/encode',
+        decode: '/api/tokenizers/nemo/decode',
+        count: '/api/tokenizers/nemo/encode',
+    },
     [tokenizers.API_TEXTGENERATIONWEBUI]: {
         encode: '/api/tokenizers/remote/textgenerationwebui/encode',
         count: '/api/tokenizers/remote/textgenerationwebui/encode',
@@ -535,6 +542,7 @@ export function getTokenizerModel() {
     const jambaTokenizer = 'jamba';
     const qwen2Tokenizer = 'qwen2';
     const commandRTokenizer = 'command-r';
+    const nemoTokenizer = 'nemo';
 
     // Assuming no one would use it for different models.. right?
     if (oai_settings.chat_completion_source == chat_completion_sources.SCALE) {
@@ -628,6 +636,9 @@ export function getTokenizerModel() {
     }
 
     if (oai_settings.chat_completion_source == chat_completion_sources.MISTRALAI) {
+        if (oai_settings.mistralai_model.includes('nemo') || oai_settings.mistralai_model.includes('pixtral')) {
+            return nemoTokenizer;
+        }
         return mistralTokenizer;
     }
 

src/endpoints/tokenizers.js

@@ -221,6 +221,7 @@ const claude_tokenizer = new WebTokenizer('src/tokenizers/claude.json');
 const llama3_tokenizer = new WebTokenizer('src/tokenizers/llama3.json');
 const commandTokenizer = new WebTokenizer('https://github.com/SillyTavern/SillyTavern-Tokenizers/raw/main/command-r.json', 'src/tokenizers/llama3.json');
 const qwen2Tokenizer = new WebTokenizer('https://github.com/SillyTavern/SillyTavern-Tokenizers/raw/main/qwen2.json', 'src/tokenizers/llama3.json');
+const nemoTokenizer = new WebTokenizer('https://github.com/SillyTavern/SillyTavern-Tokenizers/raw/main/nemo.json', 'src/tokenizers/llama3.json');
 
 const sentencepieceTokenizers = [
     'llama',
@@ -418,6 +419,10 @@ function getTokenizerModel(requestModel) {
         return 'command-r';
     }
 
+    if (requestModel.includes('nemo')) {
+        return 'nemo';
+    }
+
     // default
     return 'gpt-3.5-turbo';
 }
@@ -645,6 +650,7 @@ router.post('/claude/encode', jsonParser, createWebTokenizerEncodingHandler(clau
 router.post('/llama3/encode', jsonParser, createWebTokenizerEncodingHandler(llama3_tokenizer));
 router.post('/qwen2/encode', jsonParser, createWebTokenizerEncodingHandler(qwen2Tokenizer));
 router.post('/command-r/encode', jsonParser, createWebTokenizerEncodingHandler(commandTokenizer));
+router.post('/nemo/encode', jsonParser, createWebTokenizerEncodingHandler(nemoTokenizer));
 router.post('/llama/decode', jsonParser, createSentencepieceDecodingHandler(spp_llama));
 router.post('/nerdstash/decode', jsonParser, createSentencepieceDecodingHandler(spp_nerd));
 router.post('/nerdstash_v2/decode', jsonParser, createSentencepieceDecodingHandler(spp_nerd_v2));
@@ -657,6 +663,7 @@ router.post('/claude/decode', jsonParser, createWebTokenizerDecodingHandler(clau
 router.post('/llama3/decode', jsonParser, createWebTokenizerDecodingHandler(llama3_tokenizer));
 router.post('/qwen2/decode', jsonParser, createWebTokenizerDecodingHandler(qwen2Tokenizer));
 router.post('/command-r/decode', jsonParser, createWebTokenizerDecodingHandler(commandTokenizer));
+router.post('/nemo/decode', jsonParser, createWebTokenizerDecodingHandler(nemoTokenizer));
 
 router.post('/openai/encode', jsonParser, async function (req, res) {
     try {
@@ -707,6 +714,11 @@ router.post('/openai/encode', jsonParser, async function (req, res) {
             return handler(req, res);
         }
 
+        if (queryModel.includes('nemo')) {
+            const handler = createWebTokenizerEncodingHandler(nemoTokenizer);
+            return handler(req, res);
+        }
+
         const model = getTokenizerModel(queryModel);
         const handler = createTiktokenEncodingHandler(model);
         return handler(req, res);
@@ -765,6 +777,11 @@ router.post('/openai/decode', jsonParser, async function (req, res) {
             return handler(req, res);
         }
 
+        if (queryModel.includes('nemo')) {
+            const handler = createWebTokenizerDecodingHandler(nemoTokenizer);
+            return handler(req, res);
+        }
+
         const model = getTokenizerModel(queryModel);
         const handler = createTiktokenDecodingHandler(model);
         return handler(req, res);
@@ -835,6 +852,13 @@ router.post('/openai/count', jsonParser, async function (req, res) {
             return res.send({ 'token_count': num_tokens });
         }
 
+        if (model === 'nemo') {
+            const instance = await nemoTokenizer.get();
+            if (!instance) throw new Error('Failed to load the Nemo tokenizer');
+            num_tokens = countWebTokenizerTokens(instance, req.body);
+            return res.send({ 'token_count': num_tokens });
+        }
+
         const tokensPerName = queryModel.includes('gpt-3.5-turbo-0301') ? -1 : 1;
         const tokensPerMessage = queryModel.includes('gpt-3.5-turbo-0301') ? 4 : 3;
         const tokensPadding = 3;