Solving various NLP tasks using Transfer Learning from the pre-trained models provided by huggingface's transformers library
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Updated
Oct 25, 2020 - HTML
Solving various NLP tasks using Transfer Learning from the pre-trained models provided by huggingface's transformers library
❄️ All about my interest Papers and Review :)
A modern and lightweight NLP interface for Question-Answering systems and more. Fork this project to showcase your Python models with elegant web applications in no time!
In this Project I have used Speech Recognition tools to perform speech-to-text and text-to-speech tasks, and I leveraged pre-trained Transformers language models to give the bot some Artificial Intelligence.
ODSC East 2022 tutorial, workshop, and training prerequisites and resources will be available in this repository
Intent classification is the automatic categorization of text data based on customer goals. It is known to be a complex problem in NLP. Sequence Labelling aims to classify each token (word) in a class space C. This project addresses these two problem statements by covering the basic concepts of NLP to advanced ones. For instance, linguistics ana…
A simple python web application that allows you to easily create text with the help of a language model.
Chatbot em Python com Flask usando modelos de inteligência artificial de processamento da linguagem natural Transformers question-answering baseado num contexto customizável (fine-tuning)
A toolkit for vision-language processing to support the increasing popularity of mulit-modal transformer-based models
In this article, the factors affecting BERT's transferability is explained through visualizations
Code for the CROPLAND AI Christmas card generator
Topic detection to identify the main topics on MIT management papers
State of Art AI models you can run locally.
Some of my earliest code written in the spring of 1998 - 2005. Website was based on Hasbro's Transformers.
Detect elephant rumbles and gunshots on recordings made in the forests of central Africa and optimize the prediction process to implement on-edge.
Discussed about 4 use-cases or case studies. Discussed about the approaches and significance of these use-cases as these are different from others. There are several approaches available which can be done using LLM but here the approaches and it's significance could bring insightful approaches towards it's execution.
🐪 Converters: State-of-the-art Machine Learning for Javascript, Typescript, Node, Deno, Bun
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