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    1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic

      Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

      Jupyter Notebook 2 1

    2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic

      German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

      Python 1

    3. RNN-Text-GenerationRNN-Text-GenerationPublic

      An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

      Jupyter Notebook 1

    4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public

      Jupyter Notebook 1

    5. Deep-Convolutional-GANDeep-Convolutional-GANPublic

      Python 1

    6. LLMLLMPublic

      A Not-So-Large-Yet Language Model. A decoder-only generative transformer

      Python 2

    , 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
     blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
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;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
AdarshAcharya5 (Adarsh Acharya) · GitHub
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      Achievements
      Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
      Achievements
      Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
      
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      1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
        
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

        Jupyter Notebook
2

1

      2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
        
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

        Python
1

      3. RNN-Text-GenerationRNN-Text-GenerationPublic
        
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

        Jupyter Notebook
1

      4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
        Jupyter Notebook
1

      5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
        Python
1

      6. LLMLLMPublic
        
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

        Python
2

      
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
AdarshAcharya5 (Adarsh Acharya) · GitHub
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      View AdarshAcharya5's full-sized avatar
      5
followers
 · 10
following

        Achievements
        Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
        Achievements
        Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
        
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        1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
          
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

          Jupyter Notebook
2

1

        2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
          
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

          Python
1

        3. RNN-Text-GenerationRNN-Text-GenerationPublic
          
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

          Jupyter Notebook
1

        4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
          Jupyter Notebook
1

        5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
          Python
1

        6. LLMLLMPublic
          
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

          Python
2

        
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
AdarshAcharya5 (Adarsh Acharya) · GitHub
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        View AdarshAcharya5's full-sized avatar
        5
followers
 · 10
following

          Achievements
          Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
          Achievements
          Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
          
Block or report AdarshAcharya5

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          1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
            
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

            Jupyter Notebook
2

1

          2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
            
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

            Python
1

          3. RNN-Text-GenerationRNN-Text-GenerationPublic
            
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

            Jupyter Notebook
1

          4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
            Jupyter Notebook
1

          5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
            Python
1

          6. LLMLLMPublic
            
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

            Python
2

          
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
AdarshAcharya5 (Adarsh Acharya) · GitHub
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          View AdarshAcharya5's full-sized avatar
          5
followers
 · 10
following

            Achievements
            Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
            Achievements
            Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
            
Block or report AdarshAcharya5

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            1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
              
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

              Jupyter Notebook
2

1

            2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
              
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

              Python
1

            3. RNN-Text-GenerationRNN-Text-GenerationPublic
              
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

              Jupyter Notebook
1

            4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
              Jupyter Notebook
1

            5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
              Python
1

            6. LLMLLMPublic
              
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

              Python
2

            
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
AdarshAcharya5 (Adarsh Acharya) · GitHub
            Skip to content
            View AdarshAcharya5's full-sized avatar
            5
followers
 · 10
following

              Achievements
              Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
              Achievements
              Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
              
Block or report AdarshAcharya5

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              1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
                
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

                Jupyter Notebook
2

1

              2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
                
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

                Python
1

              3. RNN-Text-GenerationRNN-Text-GenerationPublic
                
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

                Jupyter Notebook
1

              4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
                Jupyter Notebook
1

              5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
                Python
1

              6. LLMLLMPublic
                
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

                Python
2

              
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
})();
AdarshAcharya5 (Adarsh Acharya) · GitHub
              Skip to content
              View AdarshAcharya5's full-sized avatar
              5
followers
 · 10
following

                Achievements
                Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
                Achievements
                Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: Quickdraw
                
Block or report AdarshAcharya5

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                1. Complete-Transformer-ArchitectureComplete-Transformer-ArchitecturePublic
                  
Complete Architecture of Transformer Model with PyTorch, proposed in the paper "Attention is all you need" : https://arxiv.org/pdf/1706.03762.pdf, the crux of sequence models like GPT.

                  Jupyter Notebook
2

1

                2. German-to-English-PyTorch-TransformersGerman-to-English-PyTorch-TransformersPublic
                  
German to English translation with Seq2Seq Transformers \w PyTorch. Dataset -> Multi30k

                  Python
1

                3. RNN-Text-GenerationRNN-Text-GenerationPublic
                  
An rnn with Adam optimizer developed with only numpy and vanilla python. Trainable on any simple txt dataset.

                  Jupyter Notebook
1

                4. Voice-Assistant-GPT3.5Voice-Assistant-GPT3.5Public
                  Jupyter Notebook
1

                5. Deep-Convolutional-GANDeep-Convolutional-GANPublic
                  Python
1

                6. LLMLLMPublic
                  
A Not-So-Large-Yet Language Model. A decoder-only generative transformer

                  Python
2