[Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197

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[Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
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tarekgh
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TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
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ML.NET 5.0

Description

@nietras
nietras
opened on Jul 22, 2024

Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:

https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main

Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?

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    , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
     blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

    Skip to content
    [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
    Open
    Open
    [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
    Assignees
    tarekgh
    Labels
    TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
    Milestone
    ML.NET 5.0
    Description
    @nietras
    nietras
    opened on Jul 22, 2024
    Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
    https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
    Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
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    Metadata
    Assignees
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    TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

      Skip to content
      [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
      Open
      Open
      [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
      Assignees
      tarekgh
      Labels
      TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
      Milestone
      ML.NET 5.0
      Description
      @nietras
      nietras
      opened on Jul 22, 2024
      Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
      https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
      Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
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      Metadata
      Assignees
      Labels
      TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
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      No type
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      No projects
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        None yet
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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        [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
        Open
        Open
        [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
        Assignees
        tarekgh
        Labels
        TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
        Milestone
        ML.NET 5.0
        Description
        @nietras
        nietras
        opened on Jul 22, 2024
        Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
        https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
        Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
        Metadata
        Metadata
        Assignees
        Labels
        TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
        Type
        No type
        Projects
        No projects
          Milestone
          Relationships
          None yet
          Development
          No branches or pull requests
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

          Skip to content
          [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
          Open
          Open
          [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
          Assignees
          tarekgh
          Labels
          TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
          Milestone
          ML.NET 5.0
          Description
          @nietras
          nietras
          opened on Jul 22, 2024
          Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
          https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
          Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
          Metadata
          Metadata
          Assignees
          Labels
          TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
          Type
          No type
          Projects
          No projects
            Milestone
            Relationships
            None yet
            Development
            No branches or pull requests
            Issue actions
            
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

            Skip to content
            [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
            Open
            Open
            [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
            Assignees
            tarekgh
            Labels
            TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
            Milestone
            ML.NET 5.0
            Description
            @nietras
            nietras
            opened on Jul 22, 2024
            Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
            https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
            Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
            Metadata
            Metadata
            Assignees
            Labels
            TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
            Type
            No type
            Projects
            No projects
              Milestone
              Relationships
              None yet
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              No branches or pull requests
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
              Open
              Open
              [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
              Assignees
              tarekgh
              Labels
              TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
              Milestone
              ML.NET 5.0
              Description
              @nietras
              nietras
              opened on Jul 22, 2024
              Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
              https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
              Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
              Metadata
              Metadata
              Assignees
              Labels
              TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
              Type
              No type
              Projects
              No projects
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                Relationships
                None yet
                Development
                No branches or pull requests
                Issue actions
                
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

                Skip to content
                [Tokenizers] How to load HF based tokenizers e.g. SmolLM #7197
                Open
                Open
                [Tokenizers] How to load HF based tokenizers e.g. SmolLM#7197
                Assignees
                tarekgh
                Labels
                TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
                Milestone
                ML.NET 5.0
                Description
                @nietras
                nietras
                opened on Jul 22, 2024
                Often LLM models are distributed on HuggingFace or similar where tokenizers are presumed created via transformers library. This often contains a bunch of json/txt files. I have found it hard to then now how to create a ML.Tokenizer from that. For example how would one create a tokenizer for:
                https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct/tree/main
                Could there be a getting started document detailing how to load tokenizers from such files and how to identify what to use to load these?
                Metadata
                Metadata
                Assignees
                Labels
                TokenizersdocumentationRelated to documentation of ML.NETenhancementNew feature or requestquestionFurther information is requested
                Type
                No type
                Projects
                No projects
                  Milestone
                  Relationships
                  None yet
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                  No branches or pull requests
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