{"id":1,"date":"2024-11-26T08:36:42","date_gmt":"2024-11-26T08:36:42","guid":{"rendered":"http:\/\/localhost\/wordpress\/valancelabs\/?p=1"},"modified":"2025-05-20T12:28:42","modified_gmt":"2025-05-20T12:28:42","slug":"introducing-openqdc-the-open-source-hub-of-ml-ready-quantum-datasets","status":"publish","type":"post","link":"https:\/\/www.valencelabs.com\/fr\/introducing-openqdc-the-open-source-hub-of-ml-ready-quantum-datasets\/","title":{"rendered":"Pr\u00e9sentation d\u2019OpenQDC \u2013 L'hub open-source de donn\u00e9es quantiques pr\u00eates pour le ML"},"content":{"rendered":"<div class=\"fifty_fifty\">\n    <div class=\"container\">\n        <div class=\"left__col\">\n            <h2>Introduction<\/h2>\n                    <\/div>\n        <div class=\"right__col\">\n            <div class=\"desc\">\n                <p>Nous avons organis\u00e9 et consolid\u00e9 plus de 40 ensembles de donn\u00e9es de m\u00e9canique quantique (QM), couvrant 1,5\u202fmilliard de g\u00e9om\u00e9tries sur 70 esp\u00e8ces d\u2019atomes et plus de 250 m\u00e9thodes QM, dans un hub unique et accessible appel\u00e9\u00a0<a href=\"https:\/\/www.openqdc.io\/\">OpenQDC<\/a>. C\u2019est open source et les ensembles de donn\u00e9es sont accessibles via la\u00a0<a href=\"https:\/\/docs.openqdc.io\/stable\/tutorials\/usage.html\">biblioth\u00e8que Python OpenQDC<\/a>. Installez\u2011le avec pip (pip install OpenQDC) pour commencer \u00e0 t\u00e9l\u00e9charger et utiliser divers ensemble de donn\u00e9es QM en une seule ligne de code.<\/p>\n<p>Github page:\u00a0<a href=\"https:\/\/github.com\/valence-labs\/openQDC\" target=\"_blank\" rel=\"noopener\">https:\/\/github.com\/valence-labs\/openQDC<\/a>\u2028\u2028<\/p>\n<p>Website:\u00a0<a href=\"https:\/\/www.openqdc.io\/\" target=\"_blank\" rel=\"noopener\">https:\/\/www.openqdc.io\/<\/a><\/p>            <\/div>\n        <\/div>\n    <\/div>\n<\/div>\n\n<div class=\"wp-block-image is-style-default\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"920\" height=\"238\" src=\"https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/Frame-2087325914.png\" alt=\"\" class=\"wp-image-80\" srcset=\"https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/Frame-2087325914.png 920w, https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/Frame-2087325914-300x78.png 300w, https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/Frame-2087325914-768x199.png 768w, https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/Frame-2087325914-18x5.png 18w\" sizes=\"auto, (max-width: 920px) 100vw, 920px\" \/><\/figure>\n<\/div>\n\n\n<div class=\"fifty_fifty\">\n    <div class=\"container\">\n        <div class=\"left__col\">\n            <h2>D\u00e9fis li\u00e9s aux ensembles de <span>donn\u00e9es MQ<\/span><\/h2>\n                    <\/div>\n        <div class=\"right__col\">\n            <div class=\"desc\">\n                <p>D\u00e9velopper des MLIP (potentiels interatomiques pilot\u00e9s par apprentissage automatique) robustes n\u00e9cessite d\u2019\u00e9normes quantit\u00e9s de donn\u00e9es de m\u00e9canique quantique (MQ). Malheureusement, il y a un manque d\u2019ensemble de donn\u00e9es standardis\u00e9es et pr\u00eats \u00e0 l\u2019emploi (\u00ab\u202fplug\u2011and\u2011play\u202f\u00bb) pouvant \u00eatre utilis\u00e9s pour entra\u00eener et tester de nouveaux algorithmes de ML, ce qui entrave le prototypage de nouvelles recherches dans ce domaine.<\/p>\n<p>Les ensembles de donn\u00e9es QM existants couvrent diverses m\u00e9thodes et diff\u00e9rents espaces chimiques. Ils sont \u00e9galement \u00e9parpill\u00e9s dans plusieurs d\u00e9p\u00f4ts (p.\u202fex. QCArchive, ColabFit, NablaDFT, GEOM) avec des m\u00e9tadonn\u00e9es manquantes (p.\u202fex. niveau de th\u00e9orie et unit\u00e9s), ajoutant une couche de complexit\u00e9 suppl\u00e9mentaire \u00e0 leur utilisation. Cela entrave non seulement l\u2019adoption et l\u2019utilit\u00e9 des donn\u00e9es, mais aussi les opportunit\u00e9s de collaboration entre physiciens, chimistes, experts en ML et sp\u00e9cialistes d\u2019autres disciplines, limitant les avanc\u00e9es de la recherche en ML.<\/p>            <\/div>\n        <\/div>\n    <\/div>\n<\/div>\n\n\n<div class=\"wp-block-group blurred_container\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"title__desc\">\n    <div class=\"container\">\n        <h2>Pr\u00e9sentation de <span>OpenQDC<\/span><\/h2>\n                    <div class=\"desc\">\n                <p>Avec OpenQDC, nous visons \u00e0 unifier et standardiser les ensembles de donn\u00e9es bien connus afin de faire progresser la recherche sur les MLIP. Nous avons rassembl\u00e9 des ensembles de donn\u00e9s publics et calcul\u00e9 des m\u00e9tadonn\u00e9es essentielles qui manquaient mais n\u00e9cessaires \u00e0 un traitement pr\u00e9cis des donn\u00e9es (par\u202fexemple l\u2019\u00e9nergie, la distance, les unit\u00e9s de force, et les \u00e9nergies d\u2019atomes isol\u00e9s).<\/p>            <\/div>\n            <\/div>\n<\/div>\n\n\n<figure class=\"wp-block-video\"><video height=\"676\" style=\"aspect-ratio: 1280 \/ 676;\" width=\"1280\" autoplay loop muted src=\"https:\/\/www.valencelabs.com\/wp-content\/uploads\/2025\/04\/649f91f882c085941222eb58_673f9808e0c96f6d14c7acbe_OpenQDC-Video-1-transcode.mp4\" playsinline><\/video><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Les m\u00e9thodes QM et unit\u00e9s physiques sont rigoureusement annot\u00e9es, valid\u00e9es, et utilis\u00e9es pour fournir des statistiques utiles, des m\u00e9thodes de normalisation et des conversions, offrant des moyens efficaces d\u2019utiliser de multiple ensemble de donn\u00e9es de mani\u00e8re nouvelle et auparavant impossibles pour progresser davantage la fronti\u00e8re de la recherche MLIP.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Dataset<\/th><th># conf.<\/th><th># E<\/th><th># F<\/th><th># Atom type<\/th><th>Atom Min\/Max<\/th><th>Dataset<\/th><th># conf.<\/th><th># E<\/th><th># F<\/th><th># Atom type<\/th><th>Atom Min\/Max<\/th><\/tr><\/thead><tbody><tr><td>ANI-1<\/td><td>22,057,374<\/td><td>1<\/td><td>0<\/td><td>4<\/td><td>2\/26<\/td><td>ANI-1x<\/td><td>4,956,005<\/td><td>8<\/td><td>2<\/td><td>4<\/td><td>2\/63<\/td><\/tr><tr><td>ANI-1ccx<\/td><td>489,571<\/td><td>4<\/td><td>0<\/td><td>4<\/td><td>2\/63<\/td><td>ANI-2x<\/td><td>9,651,712<\/td><td>1<\/td><td>1<\/td><td>4<\/td><td>22\/63<\/td><\/tr><tr><td>COMP6<\/td><td>101,352<\/td><td>1<\/td><td>0<\/td><td>4<\/td><td>6\/312<\/td><td>GDML<\/td><td>3,875,468<\/td><td>3<\/td><td>3<\/td><td>4<\/td><td>9\/24<\/td><\/tr><tr><td>GEOM<\/td><td>33,078,483<\/td><td>1<\/td><td>1<\/td><td>6<\/td><td>3\/181<\/td><td>ISO17<\/td><td>640,982<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>1\/19<\/td><\/tr><tr><td>MD22<\/td><td>223,442<\/td><td>1<\/td><td>1<\/td><td>4<\/td><td>42\/370<\/td><td>Molecule3D<\/td><td>3,899,647<\/td><td>1<\/td><td>0<\/td><td>8<\/td><td>1\/137<\/td><\/tr><tr><td>MultixQM9<\/td><td>133,631<\/td><td>229<\/td><td>0<\/td><td>5<\/td><td>3\/29<\/td><td>NablaDFT<\/td><td>1,275,340<\/td><td>1<\/td><td>1<\/td><td>8<\/td><td>8\/57<\/td><\/tr><tr><td>OrbNet D.<\/td><td>2,338,889<\/td><td>2<\/td><td>0<\/td><td>17<\/td><td>2\/74<\/td><td>Pub. PM6<\/td><td>189,890,155<\/td><td>1<\/td><td>0<\/td><td>70<\/td><td>1\/215<\/td><\/tr><tr><td>Pub. B3lyp<\/td><td>85,915,773<\/td><td>1<\/td><td>0<\/td><td>70<\/td><td>1\/215<\/td><td>QM7<\/td><td>7165<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>2\/23<\/td><\/tr><tr><td>QM7-X<\/td><td>4,195,192<\/td><td>2<\/td><td>1<\/td><td>6<\/td><td>4\/23<\/td><td>QM8<\/td><td>21,786<\/td><td>2<\/td><td>0<\/td><td>5<\/td><td>3\/8<\/td><\/tr><tr><td>QM9<\/td><td>133,885<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>3\/9<\/td><td>Qmugs<\/td><td>1,992,984<\/td><td>2<\/td><td>0<\/td><td>10<\/td><td>4\/228<\/td><\/tr><tr><td>RevMD17<\/td><td>999,988<\/td><td>1<\/td><td>1<\/td><td>4<\/td><td>9\/24<\/td><td>SN2 React.<\/td><td>452,709<\/td><td>1<\/td><td>0<\/td><td>6<\/td><td>2\/6<\/td><\/tr><tr><td>Sol. Prot.<\/td><td>2,731,180<\/td><td>1<\/td><td>1<\/td><td>5<\/td><td>2\/120<\/td><td>Spice<\/td><td>1,110,165<\/td><td>1<\/td><td>1<\/td><td>15<\/td><td>2\/110<\/td><\/tr><tr><td>SpiceV2<\/td><td>2,008,628<\/td><td>1<\/td><td>1<\/td><td>17<\/td><td>2\/110<\/td><td>tmQM<\/td><td>86,665<\/td><td>1<\/td><td>0<\/td><td>44<\/td><td>5\/569<\/td><\/tr><tr><td>Transition1x<\/td><td>9,654,813<\/td><td>1<\/td><td>1<\/td><td>4<\/td><td>4\/23<\/td><td>WaterClusters<\/td><td>4,464,740<\/td><td>1<\/td><td>2<\/td><td>2<\/td><td>9\/90<\/td><\/tr><tr><td>Alchemy<\/td><td>202,579<\/td><td>1<\/td><td>0<\/td><td>4<\/td><td>11\/38<\/td><td>ANICCXv2<\/td><td>489,457<\/td><td>6<\/td><td>0<\/td><td>4<\/td><td>2\/55<\/td><\/tr><tr><td>BPA<\/td><td>13,993<\/td><td>1<\/td><td>1<\/td><td>4<\/td><td>27\/27<\/td><td>MACEOFF<\/td><td>1,001,200<\/td><td>1<\/td><td>1<\/td><td>10<\/td><td>3\/150<\/td><\/tr><tr><td>QM7xv2<\/td><td>4,195,192<\/td><td>3<\/td><td>1<\/td><td>6<\/td><td>4\/23<\/td><td>QMugsv2<\/td><td>1,992,941<\/td><td>3<\/td><td>0<\/td><td>10<\/td><td>4\/228<\/td><\/tr><tr><td>QM7b<\/td><td>7211<\/td><td>76<\/td><td>0<\/td><td>6<\/td><td>4\/60<\/td><td>SpiceLv2<\/td><td>2,004,893<\/td><td>3<\/td><td>1<\/td><td>17<\/td><td>2\/110<\/td><\/tr><tr><td>SCANWater<\/td><td>322<\/td><td>19<\/td><td>0<\/td><td>8<\/td><td>1\/23<\/td><td>VQMd24<\/td><td>1,104,982<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>1\/21<\/td><\/tr><tr><td>PtrFrags<\/td><td>2,731,986<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>2\/120<\/td><td>MDDataset<\/td><td>11,819<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>162\/321<\/td><\/tr><tr><td>QM1B<\/td><td>1,000,000,000<\/td><td>1<\/td><td>0<\/td><td>5<\/td><td>9\/11<\/td><td>DESSM<\/td><td>4,955,938<\/td><td><\/td><td><\/td><td><\/td><td><\/td><\/tr><tr><td><strong>Potential Total<\/strong><\/td><td>1,400,126,279<\/td><td>395<\/td><td>16<\/td><td>70<\/td><td>1\/370<\/td><td><\/td><td><\/td><td><\/td><td><\/td><td><\/td><td><\/td><\/tr><tr><td>DES370K<\/td><td>370,959<\/td><td>14<\/td><td>0<\/td><td>2<\/td><td>2\/44<\/td><td>DESSM<\/td><td>4,955,938<\/td><td>17<\/td><td>0<\/td><td>14<\/td><td>2\/34<\/td><\/tr><tr><td>DESS86<\/td><td>66<\/td><td>17<\/td><td>0<\/td><td>4<\/td><td>6\/34<\/td><td>DESS86x8<\/td><td>528<\/td><td>17<\/td><td>0<\/td><td>4<\/td><td>6\/34<\/td><\/tr><tr><td>Metcalf<\/td><td>13,415<\/td><td>5<\/td><td>0<\/td><td>4<\/td><td>12\/41<\/td><td>X40<\/td><td>40<\/td><td>5<\/td><td>0<\/td><td>9<\/td><td>7\/25<\/td><\/tr><tr><td>L7<\/td><td>7<\/td><td>8<\/td><td>0<\/td><td>4<\/td><td>48\/112<\/td><td>Splinter<\/td><td>1,677,830<\/td><td>20<\/td><td>0<\/td><td>10<\/td><td>2\/51<\/td><\/tr><tr><td><strong>Interaction Total<\/strong><\/td><td>7,018,783<\/td><td>0<\/td><td>20<\/td><td>2<\/td><td>2\/112<\/td><td><\/td><td><\/td><td><\/td><td><\/td><td><\/td><td><\/td><\/tr><\/tbody><\/table><\/figure>\n<\/div><\/div>\n\n\n\n<div class=\"fifty_fifty\">\n    <div class=\"container\">\n        <div class=\"left__col\">\n            <h2>La biblioth\u00e8que <span>OpenQDC<\/span><\/h2>\n                    <\/div>\n        <div class=\"right__col\">\n            <div class=\"desc\">\n                <p>La biblioth\u00e8que Python OpenQDC facilite le travail avec tous les ensembles de donn\u00e9es quantiques du hub. C\u2019est un paquetage visant \u00e0 fournir un moyen simple et efficace pour t\u00e9l\u00e9charger, charger et exploiter divers ensembles de donn\u00e9es. Vous pouvez t\u00e9l\u00e9charger des ensembles de donn\u00e9es avec une seule ligne de code.<\/p>\n<ul>\n<li>Une API (Application Programming Interfaces \/ Interfaces de programmation d'applications) pythonique simple: La simplicit\u00e9 de l\u2019interface Python garantit une facilit\u00e9 d\u2019utilisation, ce qui la rend parfaite pour un prototypage rapide.<\/li>\n<li>Pr\u00eat pour le ML: Vous ne manipulez que des objets torch.Tensor, jax.Array ou numpy.Array.<\/li>\n<li>Pr\u00eat pour le quantique: Les m\u00e9thodes quantiques utilis\u00e9es par les ensemble de donn\u00e9es sont v\u00e9rifi\u00e9es et standardis\u00e9es pour fournir des valeurs compl\u00e9mentaires, des normalisations utiles et diff\u00e9rentes statistiques.<\/li>\n<li>Standardis\u00e9: Les ensembles de donn\u00e9es sont fournis dans des formats standards et performants avec des m\u00e9tadonn\u00e9es annot\u00e9es telles que des unit\u00e9s et des \u00e9tiquettes.<\/li>\n<li>La performance compte: Lecture et \u00e9criture dans plusieurs formats (memmap, zarr, xyz, etc.).<\/li>\n<li>Donn\u00e9es: Ayez acc\u00e8s \u00e0 plus de 1,5 milliard de points de donn\u00e9es.<\/li>\n<li>Open source et extensible: OpenQDC et tous ses fichiers et ensembles de donn\u00e9es sont open source; et vous pouvez ajouter votre propre ensemble de donn\u00e9es et le partager avec la communaut\u00e9 en quelques minutes seulement.<\/li>\n<\/ul>            <\/div>\n        <\/div>\n    <\/div>\n<\/div>\n\n\n<div class=\"title__desc\">\n    <div class=\"container\">\n        <h2>Getting <span>Started<\/span><\/h2>\n            <\/div>\n<\/div>\n\n  \n\n<div class=\"custom__code__block\">\n    <div class=\"container\">\n        <p>Installez OpenQDC avec pip ou conda:<\/p>\n                    <div class=\"code\">\n                <div class=\"code_container\">\n                    <p>Python<\/p>\n<p>pip install openqdc<br \/>\nor<br \/>\nconda install openqdc -c conda-forge<\/p>                <\/div>\n            <\/div>\n            <\/div>\n<\/div>\n\n  \n\n<div class=\"custom__code__block\">\n    <div class=\"container\">\n        <p>Vous \u00eates maintenant pr\u00eat\u00b7e \u00e0 utiliser tous nos ensembles de donn\u00e9es QM avec CLI pr\u00eat \u00e0 l\u2019emploi.<\/p>\n                    <div class=\"code\">\n                <div class=\"code_container\">\n                    <p>Unset<\/p>\n<p>openqdc download SpiceV2<\/p>                <\/div>\n            <\/div>\n            <\/div>\n<\/div>\n\n  \n\n<div class=\"custom__code__block\">\n    <div class=\"container\">\n        <p>Ou en utilisant l\u2019API Python.<\/p>\n                    <div class=\"code\">\n                <div class=\"code_container\">\n                    <p>Python<\/p>\n<p>from openqdc import SpiceV2\n<br \/><br \/>\n<lightblue># Automatically download the data<\/lightblue><br \/>\ndataset=SpiceV2()<\/p>                <\/div>\n            <\/div>\n            <\/div>\n<\/div>\n\n  \n\n<div class=\"custom__code__block\">\n    <div class=\"container\">\n        <p>Ci-dessous un aper\u00e7u illustrant la facilit\u00e9 d'utilisation d\u2019OpenQDC et de la mani\u00e8re dont il s'interface avec torch et torch_geometric.<\/p>\n                    <div class=\"code\">\n                <div class=\"code_container\">\n                    Python<br><br>\n\n<lightblue># Load the dataset<\/lightblue><br>\n<grey>from<\/grey> openqdc <grey>import<\/grey> MACEOFF<br>\n<grey>from<\/grey> torch.data.utils <grey>import<\/grey> DataLoader<br><br>\n\n<p>dataset=MACEOFF(energy_unit=<pink>&#8220;ang&#8221;<\/pink>,energy_unit=<pink>&#8220;kj\/mol&#8221;<\/pink>,array_format=&#8221;torch&#8221;)<\/p>\n\n<lightblue># Create the dataloader by simply passing the dataset<\/lightblue><br>\ndataloader=DataLoader(dataset, batch_size=32)<br><br>\n\n<lightblue># Do your own magic<\/lightblue><br>\n. . .                <\/div>\n            <\/div>\n            <\/div>\n<\/div>\n\n  \n\n<div class=\"custom__code__block\">\n    <div class=\"container\">\n        <p>\u00c9tant \u201cframework agnostic\u201d, OpenQDC peut s\u2019utiliser facilement avec torch_geometric, dans ce cas, nous pouvons utiliser la fonction radius_graph de torch_cluster pour cr\u00e9er un graphe.<\/p>\n                    <div class=\"code\">\n                <div class=\"code_container\">\n                    Python<br><br>\n<grey>from<\/grey> openqdc <grey>import<\/grey> SpiceV2<br>\n<grey>from<\/grey> torch_cluster <grey>import<\/grey> radius_graph<br>\n<grey>from<\/grey> torch_geometric.loader <grey>import<\/grey> DataLoader<br>\n<grey>from<\/grey> torch_geometric.data <grey>import<\/grey> Data<br>\n<br>\n<lightblue># We create a function to convert object into their graph<\/lightblue><br>\ndef <blue>to_pyg_data<\/blue>(x):\n<br><br>\n<lightblue>    # or any other techniques to build a graph (or use the smiles from the dataset)<\/lightblue><br>\n    edge_index = radius_graph(x.positions, 5)<br>\n    return Data(edge_index=edge_index, **x)<br>\n\n<br><br>\n\n<lightblue># Use the transform attribute to automatically convert your items<\/lightblue><br>\nds=SpiceV2(array_format=&#8221;torch&#8221;, distance_unit=&#8221;ang&#8221;, transform=to_pyg_data)\n<br><br>\n<lightblue># Create the pyg dataloader by simply passing the new dataset<\/lightblue><br>\nloader = DataLoader(ds, batch_size=32, shuffle=True)\n\n<br><br>\n<lightblue># Do your own magic<\/lightblue><br>\n. . .                <\/div>\n            <\/div>\n            <\/div>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\">Nous esp\u00e9rons qu\u2019OpenQDC puisse devenir une ressource importante pour la communaut\u00e9 afin de faire progresser la recherche sur les MLIP vers un avenir o\u00f9 l\u2019on entra\u00eenera des potentiels universels dot\u00e9s d\u2019une meilleure g\u00e9n\u00e9ralisabilit\u00e9 et d\u2019une plus grande robustesse.<br><br>N\u2019h\u00e9sitez pas \u00e0 partager vos commentaires ou \u00e0 contacter l\u2019\u00e9quipe Valence Labs sur&nbsp;<a href=\"https:\/\/github.com\/valence-labs\/OpenQDC\" data-type=\"link\" data-id=\"https:\/\/github.com\/valence-labs\/OpenQDC\" target=\"_blank\" rel=\"noreferrer noopener\">GitHub<\/a>,&nbsp;<a href=\"https:\/\/x.com\/valence_ai\" data-type=\"link\" data-id=\"https:\/\/x.com\/valence_ai\" target=\"_blank\" rel=\"noreferrer noopener\">X<\/a>,&nbsp;<a href=\"https:\/\/www.linkedin.com\/company\/valence-discovery\/\" data-type=\"link\" data-id=\"https:\/\/www.linkedin.com\/company\/valence-discovery\/\" target=\"_blank\" rel=\"noreferrer noopener\">LinkedIn<\/a>ou via le portail de&nbsp;<a href=\"https:\/\/portal.valencelabs.com\/\" data-type=\"link\" data-id=\"https:\/\/portal.valencelabs.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Valence !<\/a>!<\/p>\n\n\n<div class=\"blog_cta\">\n    <div class=\"container\">\n        <div class=\"bg\">\n            <img decoding=\"async\" src=\"https:\/\/www.valencelabs.com\/wp-content\/themes\/valencelabs\/src\/images\/blog_cta_bg.png\" alt=\"Backgroung image\">\n        <\/div>\n\n        <div class=\"content\">\n            <h2>Vous souhaitez <span>en savoir<\/span> plus sur OpenQDC?<\/h2>\n                            <div class=\"desc\">\n                    Contactez nos experts d\u00e8s aujourd'hui !                <\/div>\n                                        <a href=\"#\" class=\"read_more\">\n                    Nous contacter                    <svg width=\"24\" height=\"24\" viewbox=\"0 0 24 24\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n                    <path d=\"M5 12H19M19 12L13 6M19 12L13 18\" stroke=\"white\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n                    <\/svg>\n                <\/a>\n                    <\/div>\n        \n    <\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>We curated and consolidated 40+ quantum mechanics (QM) datasets, covering 1.5 billion geometries across 70 atom species and 250+ QM methods, into a single, acc&#8230;<\/p>","protected":false},"author":3,"featured_media":73,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[3],"class_list":["post-1","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Introducing OpenQDC - The Open-Source Hub of ML-Ready Quantum Datasets - Valence Labs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.valencelabs.com\/fr\/introducing-openqdc-the-open-source-hub-of-ml-ready-quantum-datasets\/\" \/>\n<meta property=\"og:locale\" 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