SLING is a parser for annotating text with frame semantic annotations. It is trained on an annotated corpus using Tensorflow and Dragnn.The parser is a general transition-based frame semantic parser using bi-directional LSTMs for input encoding and a Transition Based Recurrent Unit (TBRU) for output decoding. It is a jointly trained model using only the text tokens as input and the transition system has been designed to output frame graphs directly without any intervening symbolic representation.
natural-language-understanding natural-language-processing neural-network machine-learning jit-compiler frame-semantic-parsing nlpOpenCog is a framework for developing AI systems, especially appropriate for integrative multi-algorithm systems, and artificial general intelligence systems. Though much work remains to be done, it currently contains a functional core framework, and a number of cognitive agents at varying levels of completion, some already displaying interesting and useful functionalities alone and in combination. With the exception of MOSES and the CogServer, all of the above are in active development, are half-baked, poorly documented, mis-designed, subject to experimentation, and generally in need of love an attention. This is where experimentation and integration are taking place, and, like any laboratory, things are a bit fluid and chaotic.
agi natural-language natural-language-inference natural-language-understanding robotics robot-controller learning learning-algorithm unsupervised-learning unsupervised-machine-learning unsupervised-learning-algorithmsNode.js client library to use the Watson APIs. The examples folder has basic and advanced examples. The examples within each service assume that you already have service credentials.
ibm-watson-services language-translation conversation-service watson tone-analyzer natural-language visual-recognition personality-insights typescript conversation dialog discovery ibm natural-language-classifier natural-language-understanding speech-to-text text-to-speech tone_analyzer watson-developer-cloud wdcLudwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest. Simple commands can be used to train models both locally and in a distributed way, and to use them to predict on new data.
deep-learning deeplearning deep-neural-networks deep learning machine-learning machinelearning machine natural-language-processing natural-language-understanding natural-language natural-language-generation computer-vision python3This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece masking) referenced in Well-Read Students Learn Better: On the Importance of Pre-training Compact Models. We have shown that the standard BERT recipe (including model architecture and training objective) is effective on a wide range of model sizes, beyond BERT-Base and BERT-Large. The smaller BERT models are intended for environments with restricted computational resources. They can be fine-tuned in the same manner as the original BERT models. However, they are most effective in the context of knowledge distillation, where the fine-tuning labels are produced by a larger and more accurate teacher.
nlp natural-language-processing google tensorflow natural-language-understandingProvides an implementation of today's most used tokenizers, with a focus on performance and versatility.
nlp natural-language-processing transformers gpt language-model bert natural-language-understanding🤗 Transformers provides thousands of pretrained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation and more in over 100 languages. Its aim is to make cutting-edge NLP easier to use for everyone. 🤗 Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments.
nlp natural-language-processing tensorflow pytorch transformer speech-recognition seq2seq flax gpt pretrained-models language-models natural-language-generation nlp-library language-model bert natural-language-understanding jax xlnet pytorch-transformers model-hubThis package provides spaCy components and architectures to use transformer models via Hugging Face's transformers in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc. This release requires spaCy v3. For the previous version of this library, see the v0.6.x branch.
nlp machine-learning natural-language-processing google pytorch spacy openai transfer-learning language-model bert natural-language-understanding spacy-pipeline spacy-extension pytorch-model gpt-2 huggingface xlnetmini-batch size = 100, hidden_layers = [100, 50], lr = 0.0001. Epoch 25, total step 36400, accuracy 0.9031, cost 1.056221.
corpus chatbot qasystem natural-language-processing natural-language-understanding machine-learning dataset question-answering insurance insuranceqa-corpus-zhYou can Install AutoNLP python package via PIP. Please note you will need python >= 3.7 for AutoNLP to work properly. Please take a look at AutoNLP Documentation for a list of supported tasks and languages.
machine-learning natural-language-processing deep-learning natural-language-understanding huggingfaceJohn Snow Labs Spark-NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment. This library has been uploaded to the spark-packages repository https://spark-packages.org/package/JohnSnowLabs/spark-nlp .
nlp nlu natural-language-processing natural-language-understanding spark spark-ml pyspark machine-learning named-entity-recognition sentiment-analysis lemmatizer spell-checker tokenizer entity-extraction stemmer part-of-speech-tagger annotation-frameworkA curated list of NLP resources for Hungarian
nlp natural-language-processing text-mining information-retrieval information-extraction hungarian hungarian-language awesome awesome-list nlu natural-language-understanding opinion-mining named-entity-recognition tagger dataset nlp-resources parser corpus-linguistics computational-linguistics corpusHackernews-NLU is a sample application that uses Watson Natural Language Understanding service to analyze the contents of trending news articles on Hackernews to give information about the concepts, entities, categories, keywords, sentiment, emotion etc. about the news article. Clicking on the button below creates a IBM Code DevOps Toolchain and deploys this application to IBM Code. The manifest.yml file [included in the repo] is parsed to obtain the name of the application, configuration details, and the list of services that should be provisioned. For further details on the structure of the manifest.yml file, see the Cloud Foundry documentation.
swift-3 swift-server kitura natural-language-understanding hackernews-api ibmcodeRead this in other languages: 한êµì–´. In this developer journey we will use Jupyter notebooks in IBM Data Science experience(DSX) to augment IBM Watson Natural Language Understanding API output through configurable mechanism for text classification.
natural-language text-classification watson-natural-language ibm-developer-technology-cognitive ibmcode nlu watson natural-language-understanding dsx data-science-experience nlp natural-language-processingWelcome to Government Gazette text mining, cross linking, and codification Project (or 3gm for short) using Natural Language Processing Methods and Practices on Greek Legislation. This project aims to provide with the most recent versions of each law, i.e. an automated codex via NLP methods and practices.
government-documents legal-texts text-mining codification government-gazette nlp automation python3 gsoc-2018 natural-language-processing natural-language-understandingWelcome to my repo to build Data Science, Machine Learning, Computer Vision, Natural language Processing and Deep Learning packages from source. My Data Science environment is running from a LXC container so Tensorflow build system, bazel, must be build with its auto-sandboxing disabled.
archlinux data-science machine-learning deep-learning package tensorflow scikit-learn mxnet opencv nervana pandas cudnn cuda pytorch spacy natural-language-processing natural-language-understanding xgboost lightgbm mklThis project is java client to analyze sms using nlu. The nlu is referring to wks-model to extract entities data from sms.
natural-language-understanding watson watson-knowledge-studio watson-natural-language artificial-intelligence machine-learning ibmcodeThis is the code pattern for https://2ndopinion.mybluemix.net/. In this Code Pattern, we will create a Node.js app that takes the reviews from an online shopping website, Amazon, and feeds them into the Watson Natural Language Understanding service. The reviews will be stored in a Cloudant database. The Watson Natural Language Understanding service will show the overall sentiments of the reviews. The sample application will do all the reading of reviews for you and will give an overall insight about them. The Code Pattern can be useful to developers that are looking into processing multiple documents with Watson Natural Language Understanding.
ibmcode ibmcloud natural-language-understanding cloudfoundryPython packages will be installed by setup.sh script. Setup will download docker images, models and data files, so you have no need to download any of that by yourself.
natural-language-processing natural-language-understanding natural-language-generation dialogue-systems dialogue-agentsAlso, please do not add your name to your homework, since we try to keep review process anonymous. Please, register your project here.
deep-learning natural-language-processing natural-language-understanding
We have large collection of open source products. Follow the tags from
Tag Cloud >>
Open source products are scattered around the web. Please provide information
about the open source projects you own / you use.
Add Projects.