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","versions","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",[246,247,248,249,250,251,252,253],"policyLabels",[],"systemLabels",[],"products",[],"hasNimMetadata",{"_214":279,"_255":279,"_256":280,"_258":259},{"_214":276,"_255":277,"_256":278,"_258":259},{"_214":274,"_255":274,"_256":275,"_258":259},{"_214":270,"_255":271,"_256":272,"_258":259},{"_214":267,"_255":268,"_256":269,"_258":259},{"_214":263,"_255":264,"_256":265,"_258":259},{"_214":261,"_255":261,"_256":262,"_258":259},{"_214":254,"_255":254,"_256":257,"_258":259},"Transfer Learning","value","filter",{"_260":259,"_255":254},"category","label","field","Text Classification",{"_260":259,"_255":261},"Natural Language Understanding","uscs_natural_language_understanding",{"_260":266,"_255":264},"application","Natural Language Processing","uscs_natural_language_processing",{"_260":266,"_255":268},"Inference","soln_inference",{"_260":273,"_255":271},"technology","Finetuning",{"_260":259,"_255":274},"Conversational AI","soln_conversational_ai",{"_260":273,"_255":277},"BERT",{"_260":259,"_255":279},{"_114":1261,"_116":1262},"ngcApps",[1214],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1195":1196,"_1197":1198,"_1199":1200,"_1201":1202,"_1203":292,"_145":316,"_1204":1205,"_1206":56,"_1207":93,"_1208":93,"_1209":1210,"_1211":93,"_1212":1213},"amplitude",{"_1192":1193,"_830":-7,"_1194":31},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyZW5hYmxlUHJvZHVjdEdyb3VwaW5nQnlTdWJzY3JpcHRpb24lMjIlM0FmYWxzZSUyQyUyMmNvbnRhaW5lclNjYW5uaW5nUmVkZXNpZ25NMSUyMiUzQXRydWUlN0Q=","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1186":1187,"_1188":1189,"_1190":1191},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.10.0","defaultSearchSuggestions",{"_1070":398,"_1071":1072,"_1073":1074,"_1075":1076},"announcements",[],"consentState",{"_355":1060,"_1061":93,"_1062":31,"_1063":31,"_1064":1065},"consentConfig",{"_337":338,"_339":340,"_341":342,"_343":344,"_345":346,"_347":348,"_349":350,"_351":352,"_353":354,"_355":356},"showContactAdmin",1785034984882,[],[],[330,331,332,333,334,335],{"_45":60,"_47":71,"_49":109,"_51":-5,"_53":-5,"_55":56},{"_45":60,"_47":69,"_49":109,"_51":-5,"_53":-5,"_55":56},{"_45":60,"_47":67,"_49":109,"_51":-5,"_53":-5,"_55":56},{"_45":60,"_47":61,"_49":109,"_51":-5,"_53":-5,"_55":56},{"_45":57,"_47":58,"_49":109,"_51":-5,"_53":-5,"_55":56},{"_45":46,"_47":48,"_49":50,"_51":52,"_53":336,"_55":56},4,"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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Name	Size	Updated	Actions
text-classification-deployment.ipynbView Notebook	14.99 KB	July 28, 2021 UTC	curl wget Download
text-classification-training.ipynbView Notebook	28.55 KB	July 28, 2021 UTC	curl wget Download