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",[278,279,280,281,282,283,284,285],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_247":310,"_287":310,"_288":311,"_290":88},{"_247":307,"_287":308,"_288":309,"_290":88},{"_247":305,"_287":305,"_288":306,"_290":88},{"_247":301,"_287":302,"_288":303,"_290":88},{"_247":298,"_287":299,"_288":300,"_290":88},{"_247":294,"_287":295,"_288":296,"_290":88},{"_247":292,"_287":292,"_288":293,"_290":88},{"_247":286,"_287":286,"_288":289,"_290":88},"Transfer Learning","value","filter",{"_291":88,"_287":286},"category","field","Text Classification",{"_291":88,"_287":292},"Natural Language Understanding","uscs_natural_language_understanding",{"_291":297,"_287":295},"application","Natural Language Processing","uscs_natural_language_processing",{"_291":297,"_287":299},"Inference","soln_inference",{"_291":304,"_287":302},"technology","Finetuning",{"_291":88,"_287":305},"Conversational AI","soln_conversational_ai",{"_291":304,"_287":308},"BERT",{"_291":88,"_287":310},{"_158":1292,"_160":1293},"ngcApps",[1245],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1226":1227,"_1228":1229,"_1230":1231,"_1232":1233,"_1234":323,"_110":347,"_1235":1236,"_1237":60,"_1238":91,"_1239":91,"_1240":1241,"_1242":91,"_1243":1244},"amplitude",{"_1223":1224,"_861":-7,"_1225":35},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1217":1218,"_1219":1220,"_1221":1222},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1101":428,"_1102":1103,"_1104":1105,"_1106":1107},"announcements",[],"consentState",{"_386":1091,"_1092":91,"_1093":35,"_1094":35,"_1095":1096},"consentConfig",{"_368":369,"_370":371,"_372":373,"_374":375,"_376":377,"_378":379,"_380":381,"_382":383,"_384":385,"_386":387},"showContactAdmin",1785037812076,[],[],[361,362,363,364,365,366],{"_49":63,"_51":74,"_53":153,"_55":-5,"_57":-5,"_59":60},{"_49":63,"_51":70,"_53":153,"_55":-5,"_57":-5,"_59":60},{"_49":63,"_51":68,"_53":153,"_55":-5,"_57":-5,"_59":60},{"_49":63,"_51":64,"_53":153,"_55":-5,"_57":-5,"_59":60},{"_49":61,"_51":62,"_53":153,"_55":-5,"_57":-5,"_59":60},{"_49":50,"_51":52,"_53":54,"_55":56,"_57":367,"_59":60},5,"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
v1.1Selected	2	43.36 KB	June 9, 2021 UTC
v1.0	2	43.54 KB	February 12, 2021 UTC