What Is MegaMolBART v0.2?

This container deploys MegaMolBART model for inferencing. MegaMolBART is a model that understands chemistry and can be used for a variety of cheminformatics applications in drug discovery. The embeddings from its encoder can be used as features for predictive models. Alternatively, the encoder and decoder can be used together to generate novel molecules by sampling the model's embedding space.

Software Requirements

The MegaMolBART container is assembled with the prerequisite software for training NeMo-MegaMolBART and performing inference using a pre-trained model.

Requirements:

Linux OS
Pascal, Volta, Turing, or an NVIDIA Ampere architecture-based GPU.
Nvidia Driver
Docker

Getting Started

MegaMolBART v0.2 container encloses all prerequisites for training and inference. Please follow these steps to start MegaMolBART container for inference.

Start an instance of the Docker image using the following command:

# For Docker version 19.03 or later\ndocker run \\\n   --gpus all \\\n   --rm \\\n   -p 8888:8888 \\\n   nvcr.io/nvidia/clara/megamolbart:0.2.0\n\n\n# For Docker version 19.02 or older\ndocker run \\\n   --runtime nvidia \\\n   --rm \\\n   -p 8888:8888 \\\n   nvcr.io/nvidia/clara/megamolbart:0.2.0\n

In a browser open URL http://<<HOSTNAME/IP>>:8888

License

By pulling and using the container, you accept the terms and conditions of Apache 2.0 license

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MegaMolBART is a model that understands chemistry and can be used for a variety of cheminformatics applications in drug discovery. The embeddings from its encoder can be used as features for predictive models. Alternatively, the encoder and decoder can be used together to generate novel molecules by sampling the model's embedding space.\n\n\n## Software Requirements\n\nThe MegaMolBART container is assembled with the prerequisite software for training NeMo-MegaMolBART and performing inference using a pre-trained model.\n\nRequirements:\n- Linux OS\n- Pascal, Volta, Turing, or an NVIDIA Ampere architecture-based GPU.\n- Nvidia Driver\n- Docker\n\n## Getting Started\n\nMegaMolBART v0.2 container encloses all prerequisites for training and inference. Please follow these steps to start **MegaMolBART** container for inference.\n\n- Start an instance of the Docker image using the following command:\n\n```\n# For Docker version 19.03 or later\ndocker run \\\n --gpus all \\\n --rm \\\n -p 8888:8888 \\\n nvcr.io/nvidia/clara/megamolbart:0.2.0\n\n\n# For Docker version 19.02 or older\ndocker run \\\n --runtime nvidia \\\n --rm \\\n -p 8888:8888 \\\n nvcr.io/nvidia/clara/megamolbart:0.2.0\n```\n\n- In a browser open URL http://<>:8888\n\n## License\n\nBy pulling and using the container, you accept the terms and conditions of [Apache 2.0 license](http://www.apache.org/licenses/LICENSE-2.0)","MegaMolBART v0.2",["D",1679420772297],[255,251,193,247,253],"/api/image/nvidia/clara/containers/megamolbart_v0.2",8410709265,"hasSignedTag",[],[],[],[275],[],{"_91":276,"_124":276,"_125":277,"_127":278},"signed images",{"_129":278,"_124":276},"system",{"_160":1253,"_162":1254},"ngcApps",[1206],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1187":1188,"_1189":1190,"_1191":1192,"_1193":1194,"_1195":290,"_192":316,"_1196":1197,"_1198":51,"_1199":139,"_1200":139,"_1201":1202,"_1203":139,"_1204":1205},"amplitude",{"_1184":1185,"_829":-7,"_1186":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMiUyMiUzQWZhbHNlJTdE","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1178":1179,"_1180":1181,"_1182":1183},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1787612210569,"1.12.0","defaultSearchSuggestions",{"_1069":397,"_1070":1071,"_1072":1073,"_1074":1075},"announcements",[],"consentState",{"_355":1059,"_1060":139,"_1061":26,"_1062":26,"_1063":1064},"consentConfig",{"_337":338,"_339":340,"_341":342,"_343":344,"_345":346,"_347":348,"_349":350,"_351":352,"_353":354,"_355":356},"showContactAdmin",1787612210571,[],[],[330,331,332,333,334,335,336],{"_40":62,"_42":67,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":62,"_42":65,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":62,"_42":63,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":45,"_46":47,"_48":54,"_50":51},{"_40":41,"_42":43,"_44":64,"_46":-5,"_48":-5,"_50":51},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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