December 4, 2021 Natural Language Processing

Text Summarization using Transformer on GPU Docker Deployment

Deploying a Text Summarization NLP use case on Docker Container Utilizing Nvidia GPU, to setup the enviroment on linux machine follow up the below process, make sure you should have a good configuration system, my system specs are listed below(I am utilizing DataCrunch Servers) : GPU : 2xV100.10V Image : Ubuntu 20.04 + CUDA 11.1 Some Insights/Explorations If you’re a proper linux user make sure to setup it CUDA, cudaNN and Cuda Toolkit If you’re a WSL2 user then you […]

November 22, 2021 Natural Language Processing, NLP, Python

The NLP Cypher | 11.21.21

Hey … so have you ever deployed a state-of-the-art production level inference server? Don’t know how to do it? Well… last week, Michael Benesty dropped a bomb when he published one of the first ever detailed blogs on how to not only deploy a production level inference API but benchmarking some of the most widely used frameworks such as FastAPI and Triton servers and runtime engines such as ONNX runtime (ORT) and TensorRT (TRT). Eventually, Michael recreated Hugging Face’s ability […]

November 17, 2021 Natural Language Processing

Word Of The Day based on Natural Language Toolkit

• This Project is based on NLTK(Natural Language Toolkit) • It generates a RANDOM WORD from predefined list of words • From that random word it read out the word, it’s meaning with parts of speech,it’s antonyms,its synonyms • Using Windows Task Scheduler we make this project to run when user logged on • For IELTS enthusiats, it’s a wonderful script to improve their fluency in english GitHub View Github

November 1, 2021 Natural Language Processing, NLP, Python

The NLP Cypher | 10.31.21

The Localization Problem (LP) is a glaring dark cloud hanging over the state of affairs in applied deep learning. And acknowledging this problem, I believe, will enable us to make better use of applied AI and expand our knowledge in how the business market will form. Defining LP: There is a limit to how much large centralized language models can generalize at scale given: 1) that different users inherently have varying definitions of ground-truths due to inter-dependencies to their unique […]

October 29, 2021 Natural Language Processing

A Python modules, data sets, and tutorials supporting research and development in Natural Language Processing

NLTK — the Natural Language Toolkit — is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. NLTK requires Python version 3.5, 3.6, 3.7, or 3.8. For documentation, please visit nltk.org. Contributing Do you want to contribute to NLTK development? Great! Please read CONTRIBUTING.md for more details. See also how to contribute to NLTK. Donate Have you found the toolkit helpful? Please support NLTK development by donating to the project […]

October 20, 2021 Natural Language Processing, NLP, Python

The NLP Cypher | 10.17.21

David is killing it! Welcome back NLP peeps! Do you miss the old days? The old internet days of modem calling, static websites, you know… a time of innocence where developers were innovating the backbone of the internet at hyper speeds? Well, we are very much going thru that right now via the Web 3.0 revolution. Cryptocurrencies usually get all of the attention but there is something else at play and it involves the entire web. You see, the current […]

October 17, 2021 Natural Language Processing

sense2vec: Contextually-keyed word vectors

sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detailed word vectors. This library is a simple Python implementation for loading, querying and training sense2vec models. For more details, check out our blog post. To explore the semantic similarities across all Reddit comments of 2015 and 2019, see the interactive demo. ?Version 2.0 (for spaCy v3) out now! Read the release notes here. ✨Features

October 17, 2021 Natural Language Processing

A full spaCy pipeline and models for scientific/biomedical documents

This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds tokenization rules on top of spaCy’s rule-based tokenizer, a POS tagger and syntactic parser trained on biomedical data and an entity span detection model. Separately, there are also NER models for more specific tasks. Just looking to test out the models on your data? Check out our demo. Installation Installing scispacy requires two steps: installing the library […]

October 5, 2021 Natural Language Processing, NLP, Python

The NLP Cypher | 10.03.21

RAFT is a few-shot classification benchmark that tests language models: – across multiple domains (lit reviews, medical data, tweets, customer interaction, etc.) – on economically valuable classification tasks (someone inherently cares about the task) – with evaluation that mirrors deployment (50 labeled examples per task, info retrieval allowed, hidden test set)

September 28, 2021 Natural Language Processing

DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Art performance on all Benchmark tasks for Danish. This repository contains code for reproducing DaCy. To download the models use the DaNLP package (request pending), SpaCy (request pending) or downloading the project directly here. Reproduction the folder DaCy contains a SpaCy project which will allow for a reproduction of the results. This folder also includes the evaluation metrics on DaNE. Usage To […]

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