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)","Text Classification Notebook",["D",1680632039227],"/api/image/nvidia/tlt-jarvis/resources/textclassification_notebook","https://raw.githubusercontent.com/kbojo/images/master/TLT-Jarvis.png","bias","explainability","privacy","safetyAndSecurity",[],[304,305,306,307,308,309,310,311],[],[],[],{"_93":147,"_131":147,"_132":329,"_134":135},{"_93":326,"_131":327,"_132":328,"_134":135},{"_93":145,"_131":145,"_132":325,"_134":135},{"_93":321,"_131":322,"_132":323,"_134":135},{"_93":318,"_131":319,"_132":320,"_134":135},{"_93":314,"_131":315,"_132":316,"_134":135},{"_93":171,"_131":171,"_132":313,"_134":135},{"_93":137,"_131":137,"_132":312,"_134":135},{"_136":135,"_131":137},{"_136":135,"_131":171},"Natural Language Understanding","uscs_natural_language_understanding",{"_136":317,"_131":315},"application","Natural Language Processing","uscs_natural_language_processing",{"_136":317,"_131":319},"Inference","soln_inference",{"_136":324,"_131":322},"technology",{"_136":135,"_131":145},"Conversational AI","soln_conversational_ai",{"_136":324,"_131":327},{"_136":135,"_131":147},{"_198":1308,"_200":1309},"ngcApps",[1261],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1242":1243,"_1244":1245,"_1246":1247,"_1248":1249,"_1250":341,"_229":365,"_1251":1252,"_1253":51,"_1254":176,"_1255":176,"_1256":1257,"_1258":176,"_1259":1260},"amplitude",{"_1239":1240,"_880":-7,"_1241":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1233":1234,"_1235":1236,"_1237":1238},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1120":447,"_1121":1122,"_1123":1124,"_1125":1126},"announcements",[],"consentState",{"_404":1110,"_1111":176,"_1112":26,"_1113":26,"_1114":1115},"consentConfig",{"_386":387,"_388":389,"_390":391,"_392":393,"_394":395,"_396":397,"_398":399,"_400":401,"_402":403,"_404":405},"showContactAdmin",1785037822202,[],[],[379,380,381,382,383,384,385],{"_40":55,"_42":66,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":64,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":62,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":67,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":67,"_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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