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fixed up pytdc page
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amva13 committed Feb 8, 2025
1 parent b4b5db7 commit 25705d2
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4 changes: 2 additions & 2 deletions frontend/tdc/src/containers/Home/index.tsx
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Expand Up @@ -9,14 +9,14 @@ import SectionDemo from './SectionDemo';
const HomeContainer: React.FC = () => {
useEffect(() => {
// Update the document title client-side
handelTitle('TDC2: Multimodal ML Platform for Foundation Models in Therapeutics');
handelTitle('PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models');
}, []);

useEffect(() => {
// Update body background style client-side
if (typeof document !== 'undefined') {
const body = document.getElementsByTagName('body')[0];
if (document.title === 'TDC2: Multimodal ML Platform for Foundation Models in Therapeutics') {
if (document.title === 'PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models') {
body.style.backgroundImage =
'linear-gradient(180deg,#240044 0,#0f0240 25%,#400959 40%,#0f0240 65%,#0f0240)';
} else {
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2 changes: 1 addition & 1 deletion frontend/tdc/src/data/data-containers/data-HomeDemo1.tsx
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Expand Up @@ -62,7 +62,7 @@ export const service_single_content = [
},
{
title:'TDC.ProteinPeptide',
content:"Capturing the dynamic nature of protein-peptide interactions requires advanced sampling techniques and computational resources, making the prediction of binding affinities more complex (Antes et al., 2014). TDC-2 provides benchmarks integrating newly discovered peptides to test ML models on their ability to generalize to cutting-edge peptidomimetics.",
content:"Capturing the dynamic nature of protein-peptide interactions requires advanced sampling techniques and computational resources, making the prediction of binding affinities more complex (Antes et al., 2014). We provide benchmarks integrating newly discovered peptides to test ML models on their ability to generalize to cutting-edge peptidomimetics.",
link:'https://tdcommons.ai/multi_pred_tasks/proteinpeptide'
},
{
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2 changes: 1 addition & 1 deletion frontend/tdc/src/pages/MyApp.tsx
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Expand Up @@ -16,7 +16,7 @@ const Home: React.FC = () => {
<>
{/* Head component for metadata */}
<Head>
<meta property="og:title" content="The Commons TDC-2" />
<meta property="og:title" content="The Commons PyTDC" />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://tdcommons.ai" />
{/* Uncomment and provide a valid image URL if needed */}
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Expand Up @@ -14,7 +14,10 @@ const SecWhoWeContant = () => {
<Span />
</div>
<h4 data-aos="fade-up">TDC API-first Architecture</h4>
<p data-aos="fade-up">An unprecedented collection of continually updated heterogeneous data sources is unified under the introduced API-first-dataset architecture. This includes a multimodal single-cell RNA data atlas spanning 85M+ cells.</p>
<p data-aos="fade-up">A collection of multimodal continually updated heterogeneous data sources is unified under the
introduced &quot;API-first-dataset&quot; architecture. Inspired by API-first design, this microservice architecture is
implemented using the model-view-controller design pattern to enable multimodal data views
under a domain-specific-language.</p>
<a className="btn dream-btn mt-30" href="https://colab.research.google.com/drive/1xTgBwKUfP2b8j6Fqh28M2GUp2ScfENMX?usp=sharing" style={{borderColor: '#FFDF00'}}>CELLxGENE notebook</a>
</div>
</div>
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Expand Up @@ -15,8 +15,14 @@ const SecWhoWeContant = () => {
<Span />
<Span />
</div>
<h4 data-aos="fade-up">TDC Model Server</h4>
<p data-aos="fade-up">TDC-2 has released open source inference serving software that streamlines AI inferencing for single-cell foundation models across modalities. The TDC-2 Model Server enables access to an array of context-aware biological foundation models. A model store retrieval API provides unified access to models and weights stored in the HuggingFace Model Hub, CZ CELLxGENE fine-tuned models, and TDC storage. The model server also provides access to tokenizer functions and inference endpoints supporting PyTorch and HuggingFace Transformers.</p>
<h4 data-aos="fade-up">PyTDC Model Server</h4>
<p data-aos="fade-up">The PyTDC model server streamlines retrieval, inferencing, and training setup for an array
of context-aware biological foundation models and models spanning multiple modalities. A model store retrieval
API provides unified access to model weights stored in the Hugging Face Model Hub (https://huggingface.co/tdc),
Chan-Zuckerberg CELLxGENE Census fine-tuned models, and TDC storage. The model server also provides access to
model classes, tokenizer functions, and inference endpoints supporting PyTorch
and Hugging Face Transformers. Extracted embeddings, from either model server inference or pre-computed embedding
storage, are ready for downstream use by task-specific benchmarking modules.</p>
<a data-aos="fade-up" className="btn dream-btn mt-30" href="https://huggingface.co/tdc" style={{borderColor: '#FFDF00'}}>HF Model Hub</a>
</div>
</div>
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2 changes: 1 addition & 1 deletion frontend/tdc/src/template/HomeDemo1/SecTeam/index.tsx
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Expand Up @@ -19,7 +19,7 @@ const SecTeam: React.FC<SecTeamProps> = () => {
<div className="row">
<div className="col-12">
<SectionHeading
title="TDC-2 Team"
title="PyTDC Team"
text="To be disclosed"
color1="white"
color2="white"
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4 changes: 2 additions & 2 deletions frontend/tdc/src/template/HomeDemo1/index.tsx
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Expand Up @@ -30,14 +30,14 @@ import {

const HomeDemo1: React.FC = () => {
useEffect(() => {
handelTitle('TDC2: Multimodal ML Platform for Foundation Models in Therapeutics');
handelTitle('PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models');
}, []);

useEffect(() => {
// Set the body background image client-side
if (typeof document !== 'undefined') {
const body = document.getElementsByTagName('body')[0];
if (document.title === 'TDC2: Multimodal ML Platform for Foundation Models in Therapeutics') {
if (document.title === 'PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models') {
body.style.backgroundImage =
'linear-gradient(180deg,#240044 0,#0f0240 25%,#400959 40%,#0f0240 65%,#0f0240)';
} else {
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2 changes: 1 addition & 1 deletion static/_next/BUILD_ID
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@@ -1 +1 @@
1hpZr98Ypoo1d6nPO99F9
xLubw0YWreOxMGWKJLhC-
12 changes: 6 additions & 6 deletions static/_next/build-manifest.json
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Expand Up @@ -5,27 +5,27 @@
"devFiles": [],
"ampDevFiles": [],
"lowPriorityFiles": [
"static/1hpZr98Ypoo1d6nPO99F9/_buildManifest.js",
"static/1hpZr98Ypoo1d6nPO99F9/_ssgManifest.js"
"static/xLubw0YWreOxMGWKJLhC-/_buildManifest.js",
"static/xLubw0YWreOxMGWKJLhC-/_ssgManifest.js"
],
"rootMainFiles": [],
"rootMainFilesTree": {},
"pages": {
"/MyApp": [
"static/chunks/webpack-1301bfd2e9d5549e.js",
"static/chunks/webpack-2239791ea2adc667.js",
"static/chunks/framework-a4ddb9b21624b39b.js",
"static/chunks/main-0bc4b318dd31b414.js",
"static/chunks/pages/MyApp-9d21fcb3b680109b.js"
],
"/_app": [
"static/chunks/webpack-1301bfd2e9d5549e.js",
"static/chunks/webpack-2239791ea2adc667.js",
"static/chunks/framework-a4ddb9b21624b39b.js",
"static/chunks/main-0bc4b318dd31b414.js",
"static/css/6a0a91e39cf832a7.css",
"static/chunks/pages/_app-480b56ca73c33734.js"
"static/chunks/pages/_app-e2da57bafe27ae7b.js"
],
"/_error": [
"static/chunks/webpack-1301bfd2e9d5549e.js",
"static/chunks/webpack-2239791ea2adc667.js",
"static/chunks/framework-a4ddb9b21624b39b.js",
"static/chunks/main-0bc4b318dd31b414.js",
"static/chunks/pages/_error-fde50cb7f1ab27e0.js"
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2 changes: 1 addition & 1 deletion static/_next/cache/.rscinfo
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@@ -1 +1 @@
{"encryption.key":"fek+sRnxq11dE7rr0MF//HXJ5avyFzI0CeQWo2RD9fA=","encryption.expire_at":1740256907339}
{"encryption.key":"qZEeyMibeDXyhBLrCn7uygTCxaref4MOrBO+LgH6VI4=","encryption.expire_at":1740258660558}
2 changes: 1 addition & 1 deletion static/_next/cache/.tsbuildinfo

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2 changes: 1 addition & 1 deletion static/_next/cache/eslint/.cache_1vh55ac

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