Text Classification

Text Classification is one of the most common tasks in NLP, which is the process of categorizing the text into a group of words. By using NLP, text classification can automatically analyze text and then assign a set of predefined tags or categories based on its context. It is applied in a wide variety of applications, including sentiment analysis, spam filtering, news categorization, domain/intent detection for dialogue systems, etc.

The best place to get started with TLT - Text Classification would be the TLT - Text Classification jupyter notebooks. This resource has two notebooks included.

Training: Sample workflow for training a text classification model and export the model to a .ejrvs file
Deployment: Sample workflow to consume the .ejrvs file and deploy it to Jarvis.

If you are a seasoned Conversation AI developer we recommend installing TLT and referring to the TLT documentation for usage information.

Pre-Requisites

Please make sure to install the following before proceeding further:

python 3.6.9
docker-ce > 19.03.5
docker-API 1.40
nvidia-container-toolkit > 1.3.0-1
nvidia-container-runtime > 3.4.0-1
nvidia-docker2 > 2.5.0-1
nvidia-driver >= 455.23

Note: A compatible NVIDIA GPU would be required.

Installation

We recommend that you install TLT inside a virtual environment. The steps to do the same are as follows

\nsource /bin/activate\npip install jupyter notebook # If you need to run the notebooks\n\">

virtualenv -p python3 <name of venv>\nsource <name of venv>/bin/activate\npip install jupyter notebook # If you need to run the notebooks\n

TLT is python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.

pip install nvidia-pyindex\npip install nvidia-tlt\n

To download the jupyter notebook please:

Download the samples using the ngc cli with the following command

ngc registry resource download-version \"nvidia/tlt-jarvis/textclassification_notebook:v1.0\"\n

Instantiate the jupyter notebook server

jupyter notebook --ip 0.0.0.0 --allow-root --port 8888\n

License

By downloading and using the models and resources packaged with TLT Conversational AI, you would be accepting the terms of the Jarvis license

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By using NLP, text classification can automatically analyze text and then assign a set of predefined tags or categories based on its context. It is applied in a wide variety of applications, including sentiment analysis, spam filtering, news categorization, domain/intent detection for dialogue systems, etc.\n\nThe best place to get started with TLT - Text Classification would be the TLT - Text Classification jupyter notebooks. This resource has two notebooks included.\n\n1. Training: Sample workflow for training a text classification model and export the model to a `.ejrvs` file\n2. Deployment: Sample workflow to consume the `.ejrvs` file and deploy it to Jarvis.\n\nIf you are a seasoned Conversation AI developer we recommend installing TLT and referring to the [TLT documentation](https://docs.nvidia.com/TLT/tlt-user-guide/text/overview.html) for usage information.\n\n## Pre-Requisites\n\nPlease make sure to install the following before proceeding further:\n\n* python 3.6.9\n* docker-ce > 19.03.5\n* docker-API 1.40\n* nvidia-container-toolkit > 1.3.0-1\n* nvidia-container-runtime > 3.4.0-1\n* nvidia-docker2 > 2.5.0-1\n* nvidia-driver >= 455.23\n\n*Note: A compatible NVIDIA GPU would be required.*\n\n## Installation\n\nWe recommend that you install TLT inside a virtual environment. The steps to do the same are as follows \n\n```sh\nvirtualenv -p python3 \nsource /bin/activate\npip install jupyter notebook # If you need to run the notebooks\n```\n\nTLT is python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.\n\n```sh\npip install nvidia-pyindex\npip install nvidia-tlt\n```\n\nTo download the jupyter notebook please:\n\n1. Download the samples using the ngc cli with the following command\n\n```sh\nngc registry resource download-version \"nvidia/tlt-jarvis/textclassification_notebook:v1.0\"\n```\n\n2. Instantiate the jupyter notebook server\n\n```sh\njupyter notebook --ip 0.0.0.0 --allow-root --port 8888\n```\n\n## License\n\nBy downloading and using the models and resources packaged with TLT Conversational AI, you would be accepting the terms of the Jarvis [license](https://developer.nvidia.com/ngc/nvidia-jarvis-license)","displayName","Text Classification Notebook",["D",1680632039227],"publisher","NVIDIA","latestVersion","collectionCounts","imageUrl","/api/image/nvidia/tlt-jarvis/resources/textclassification_notebook","rawImageUrl","https://raw.githubusercontent.com/kbojo/images/master/TLT-Jarvis.png","canGuestDownload","latestVersionSizeInBytes","licenseTerms","isMultinodeEnabled","isMultiArchitecture","bias","explainability","privacy","safetyAndSecurity","featureLabels",[],"displayLabels",[276,277,278,279,280,281,282,283],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_245":308,"_285":308,"_286":309,"_288":87},{"_245":305,"_285":306,"_286":307,"_288":87},{"_245":303,"_285":303,"_286":304,"_288":87},{"_245":299,"_285":300,"_286":301,"_288":87},{"_245":296,"_285":297,"_286":298,"_288":87},{"_245":292,"_285":293,"_286":294,"_288":87},{"_245":290,"_285":290,"_286":291,"_288":87},{"_245":284,"_285":284,"_286":287,"_288":87},"Transfer Learning","value","filter",{"_289":87,"_285":284},"category","field","Text Classification",{"_289":87,"_285":290},"Natural Language Understanding","uscs_natural_language_understanding",{"_289":295,"_285":293},"application","Natural Language Processing","uscs_natural_language_processing",{"_289":295,"_285":297},"Inference","soln_inference",{"_289":302,"_285":300},"technology","Finetuning",{"_289":87,"_285":303},"Conversational AI","soln_conversational_ai",{"_289":302,"_285":306},"BERT",{"_289":87,"_285":308},{"_157":1288,"_159":1289},"ngcApps",[1241],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1222":1223,"_1224":1225,"_1226":1227,"_1228":1229,"_1230":321,"_109":345,"_1231":1232,"_1233":60,"_1234":90,"_1235":90,"_1236":1237,"_1238":90,"_1239":1240},"amplitude",{"_1219":1220,"_857":-7,"_1221":35},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1213":1214,"_1215":1216,"_1217":1218},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1097":424,"_1098":1099,"_1100":1101,"_1102":1103},"announcements",[],"consentState",{"_382":1087,"_1088":90,"_1089":35,"_1090":35,"_1091":1092},"consentConfig",{"_364":365,"_366":367,"_368":369,"_370":371,"_372":373,"_374":375,"_376":377,"_378":379,"_380":381,"_382":383},"showContactAdmin",1785045402358,[],[],[359,360,361,362,363],{"_49":64,"_51":74,"_53":152,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":71,"_53":152,"_55":-5,"_57":-5,"_59":60},{"_49":64,"_51":65,"_53":152,"_55":-5,"_57":-5,"_59":60},{"_49":61,"_51":62,"_53":152,"_55":-5,"_57":-5,"_59":60},{"_49":50,"_51":52,"_53":152,"_55":-5,"_57":-5,"_59":60},"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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	Files	Compressed Size		Download
v1.1	2	43.36 KB	June 9, 2021 UTC
v1.0Selected	2	43.54 KB	February 12, 2021 UTC