Release StructureCoder DPO Training Data on Hugging Face #1

Open
Open
Release StructureCoder DPO Training Data on Hugging Face#1

Description

@NielsRogge
NielsRogge
opened on Sep 1, 2025

Hi @renhouxing 🤗

Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!

Would be awesome to make the dataset available on 🤗 , so that people can do:

fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")

See here for a guide: https://huggingface.co/docs/datasets/loading.
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.

Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.

Let me know if you're interested/need any help regarding this!

Cheers,

Niels
ML Engineer @ HF 🤗

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

      Skip to content
      Release StructureCoder DPO Training Data on Hugging Face #1
      Open
      Open
      Release StructureCoder DPO Training Data on Hugging Face#1
      Description
      @NielsRogge
      NielsRogge
      opened on Sep 1, 2025
      Hi @renhouxing 🤗
      Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
      
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
      
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
      It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
      
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
      Would be awesome to make the dataset available on 🤗 , so that people can do:
      fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
      See here for a guide: https://huggingface.co/docs/datasets/loading.
      
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
      Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
      Let me know if you're interested/need any help regarding this!
      Cheers,
      Niels
      
ML Engineer @ HF 🤗
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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");
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

          Skip to content
          Release StructureCoder DPO Training Data on Hugging Face #1
          Open
          Open
          Release StructureCoder DPO Training Data on Hugging Face#1
          Description
          @NielsRogge
          NielsRogge
          opened on Sep 1, 2025
          Hi @renhouxing 🤗
          Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
          
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
          
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
          It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
          
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
          Would be awesome to make the dataset available on 🤗 , so that people can do:
          fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
          See here for a guide: https://huggingface.co/docs/datasets/loading.
          
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
          Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
          Let me know if you're interested/need any help regarding this!
          Cheers,
          Niels
          
ML Engineer @ HF 🤗
          Metadata
          Metadata
          Assignees
          No one assigned
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            No labels
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              No branches or pull requests
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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");
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              Release StructureCoder DPO Training Data on Hugging Face #1
              Open
              Open
              Release StructureCoder DPO Training Data on Hugging Face#1
              Description
              @NielsRogge
              NielsRogge
              opened on Sep 1, 2025
              Hi @renhouxing 🤗
              Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
              
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
              
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
              It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
              
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
              Would be awesome to make the dataset available on 🤗 , so that people can do:
              fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
              See here for a guide: https://huggingface.co/docs/datasets/loading.
              
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
              Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
              Let me know if you're interested/need any help regarding this!
              Cheers,
              Niels
              
ML Engineer @ HF 🤗
              Metadata
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              No one assigned
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                  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");
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} 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
                  Release StructureCoder DPO Training Data on Hugging Face #1
                  Open
                  Open
                  Release StructureCoder DPO Training Data on Hugging Face#1
                  Description
                  @NielsRogge
                  NielsRogge
                  opened on Sep 1, 2025
                  Hi @renhouxing 🤗
                  Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
                  
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
                  
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
                  It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
                  
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
                  Would be awesome to make the dataset available on 🤗 , so that people can do:
                  fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
                  See here for a guide: https://huggingface.co/docs/datasets/loading.
                  
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
                  Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
                  Let me know if you're interested/need any help regarding this!
                  Cheers,
                  Niels
                  
ML Engineer @ HF 🤗
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
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                    No type
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                      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");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                      Skip to content
                      Release StructureCoder DPO Training Data on Hugging Face #1
                      Open
                      Open
                      Release StructureCoder DPO Training Data on Hugging Face#1
                      Description
                      @NielsRogge
                      NielsRogge
                      opened on Sep 1, 2025
                      Hi @renhouxing 🤗
                      Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
                      
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
                      
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
                      It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
                      
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
                      Would be awesome to make the dataset available on 🤗 , so that people can do:
                      fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
                      See here for a guide: https://huggingface.co/docs/datasets/loading.
                      
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
                      Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
                      Let me know if you're interested/need any help regarding this!
                      Cheers,
                      Niels
                      
ML Engineer @ HF 🤗
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
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                          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");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                          Skip to content
                          Release StructureCoder DPO Training Data on Hugging Face #1
                          Open
                          Open
                          Release StructureCoder DPO Training Data on Hugging Face#1
                          Description
                          @NielsRogge
                          NielsRogge
                          opened on Sep 1, 2025
                          Hi @renhouxing 🤗
                          Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
                          
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
                          
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
                          It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
                          
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
                          Would be awesome to make the dataset available on 🤗 , so that people can do:
                          fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
                          See here for a guide: https://huggingface.co/docs/datasets/loading.
                          
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
                          Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
                          Let me know if you're interested/need any help regarding this!
                          Cheers,
                          Niels
                          
ML Engineer @ HF 🤗
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
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                              No branches or pull requests
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, '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
                              Release StructureCoder DPO Training Data on Hugging Face #1
                              Open
                              Open
                              Release StructureCoder DPO Training Data on Hugging Face#1
                              Description
                              @NielsRogge
                              NielsRogge
                              opened on Sep 1, 2025
                              Hi @renhouxing 🤗
                              Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2508.19532.
                              
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
                              
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.
                              It'd be great to make the processed DPO training data used in StructureCoder available on the 🤗 hub, to improve its discoverability/visibility.
                              
We can add tags so that people find it when filtering https://huggingface.co/datasets. I see that your model checkpoints (StructureCoder-1.5B, StructureCoder-3B, StructureCoder-7B) are already on the Hub, which is fantastic!
                              Would be awesome to make the dataset available on 🤗 , so that people can do:
                              fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org-or-username/your-dataset")
                              See here for a guide: https://huggingface.co/docs/datasets/loading.
                              
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.
                              Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
                              Let me know if you're interested/need any help regarding this!
                              Cheers,
                              Niels
                              
ML Engineer @ HF 🤗
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