Update index.html
Browse files- index.html +14 -30
index.html
CHANGED
@@ -273,7 +273,7 @@
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<div class="metric-card">
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<h4>Speed Comparison</h4>
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<p>GPT-2 is faster at ~47 tok/sec compared to SnowflakeCore's ~22-23 tok/sec.</p>
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</
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</div>
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</div>
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@@ -317,14 +317,14 @@
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{
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label: 'Bigram',
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data: [0.61, 0.74, 0.63],
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backgroundColor: 'rgba(139, 233, 253, 0.7)', /*
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borderColor: 'rgba(139, 233, 253, 1)',
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borderWidth: 1
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},
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{
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label: 'Trigram',
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data: [0.74, 0.87, 0.79],
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backgroundColor: 'rgba(80, 250, 123, 0.7)', /*
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borderColor: 'rgba(80, 250, 123, 1)',
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borderWidth: 1
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}
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@@ -337,7 +337,7 @@
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legend: {
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position: 'top',
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labels: {
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color: '#e0e0e0'
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}
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},
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tooltip: {
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@@ -349,10 +349,10 @@
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scales: {
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x: {
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ticks: {
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color: '#e0e0e0'
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},
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grid: {
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color: 'rgba(255, 255, 255, 0.1)'
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}
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},
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y: {
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@@ -361,10 +361,10 @@
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title: {
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display: true,
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text: 'Distinct N-gram Ratio',
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color: '#e0e0e0'
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},
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ticks: {
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color: '#e0e0e0'
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},
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grid: {
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color: 'rgba(255, 255, 255, 0.1)'
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@@ -383,16 +383,8 @@
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datasets: [{
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label: 'Tokens per Second',
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data: [22, 23, 47],
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backgroundColor:
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'rgba(255, 184, 108, 0.7)', /* Orange for GT-Tiny2 */
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'rgba(139, 233, 253, 0.7)' /* Blue for GPT-2 */
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],
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borderColor: [
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'rgba(255, 121, 198, 1)',
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'rgba(255, 184, 108, 1)',
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'rgba(139, 233, 253, 1)'
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],
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borderWidth: 1
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}]
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},
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@@ -446,14 +438,14 @@
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{
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label: 'Bigram',
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data: [0.39, 0.26, 0.36],
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backgroundColor: 'rgba(189, 147, 249, 0.7)', /*
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borderColor: 'rgba(189, 147, 249, 1)',
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borderWidth: 1
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},
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{
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label: 'Trigram',
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data: [0.25, 0.12, 0.21],
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backgroundColor: 'rgba(255, 85, 85, 0.7)', /*
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borderColor: 'rgba(255, 85, 85, 1)',
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borderWidth: 1
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}
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@@ -512,16 +504,8 @@
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datasets: [{
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label: 'Vocabulary Diversity Ratio',
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data: [0.28, 0.34, 0.26],
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backgroundColor:
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'rgba(80, 250, 123, 0.7)', /* Green for GT-Tiny2 */
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'rgba(255, 184, 108, 0.7)' /* Orange for GPT-2 */
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],
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borderColor: [
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'rgba(241, 250, 140, 1)',
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'rgba(80, 250, 123, 1)',
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'rgba(255, 184, 108, 1)'
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],
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borderWidth: 1
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}]
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},
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<div class="metric-card">
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<h4>Speed Comparison</h4>
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<p>GPT-2 is faster at ~47 tok/sec compared to SnowflakeCore's ~22-23 tok/sec.</p>
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</p>
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</div>
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</div>
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{
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label: 'Bigram',
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data: [0.61, 0.74, 0.63],
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backgroundColor: 'rgba(139, 233, 253, 0.7)', /* Consistent light blue */
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borderColor: 'rgba(139, 233, 253, 1)',
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borderWidth: 1
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},
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{
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label: 'Trigram',
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data: [0.74, 0.87, 0.79],
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backgroundColor: 'rgba(80, 250, 123, 0.7)', /* Consistent green */
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borderColor: 'rgba(80, 250, 123, 1)',
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borderWidth: 1
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}
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legend: {
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position: 'top',
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labels: {
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color: '#e0e0e0'
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}
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},
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tooltip: {
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scales: {
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x: {
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ticks: {
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color: '#e0e0e0'
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},
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grid: {
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color: 'rgba(255, 255, 255, 0.1)'
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}
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},
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y: {
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title: {
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display: true,
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text: 'Distinct N-gram Ratio',
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color: '#e0e0e0'
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},
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ticks: {
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color: '#e0e0e0'
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},
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grid: {
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color: 'rgba(255, 255, 255, 0.1)'
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datasets: [{
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label: 'Tokens per Second',
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data: [22, 23, 47],
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backgroundColor: 'rgba(139, 233, 253, 0.7)', /* Single color for all bars */
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borderColor: 'rgba(139, 233, 253, 1)',
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borderWidth: 1
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}]
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},
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{
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label: 'Bigram',
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data: [0.39, 0.26, 0.36],
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backgroundColor: 'rgba(189, 147, 249, 0.7)', /* Consistent purple */
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borderColor: 'rgba(189, 147, 249, 1)',
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borderWidth: 1
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},
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{
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label: 'Trigram',
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data: [0.25, 0.12, 0.21],
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backgroundColor: 'rgba(255, 85, 85, 0.7)', /* Consistent red */
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borderColor: 'rgba(255, 85, 85, 1)',
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borderWidth: 1
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}
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datasets: [{
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label: 'Vocabulary Diversity Ratio',
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data: [0.28, 0.34, 0.26],
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backgroundColor: 'rgba(80, 250, 123, 0.7)', /* Single color for all bars */
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borderColor: 'rgba(80, 250, 123, 1)',
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borderWidth: 1
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}]
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},
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