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19 search results found

Practical Pytorch ⭐ 4,272

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

Flaml ⭐ 3,500

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Question_generation ⭐ 836

Neural question generation using transformers

Natural Language Processing Specialization ⭐ 624

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

Treasure Of Transformers ⭐ 541

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

Multilingual Generative Pretrained Model

Image Caption Generator ⭐ 136

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Hands On Python Natural Language Processing ⭐ 65

Oreilly Gpt Hands On Nlg ⭐ 54

This repository contains code for the O'Reilly Live Online Training for NLG & GPT

Reader Translator Generator - NMT toolkit based on pytorch

Deep Learning With Neural Networks ⭐ 11

This repo contains various use-cases of deep-learning implemented in Pytorch. It also contains summarized notes of each chapter from the book, 'Deep Learning' written by Ian Goodfellow.

Writing With Bert ⭐ 10

Using BERT for doing the task of Conditional Natural Language Generation by fine-tuning pre-trained BERT on custom dataset.

A no-code development framework—Let AI do the coding for you 🦾

Code for GenAug: Data Augmentation for Finetuning Text Generators.

Orangesum ⭐ 8

The French summarization dataset introduced in "BARThez: a Skilled Pretrained French Sequence-to-Sequence Model".

Prompting Nlp ⭐ 7

About, prompt-based few-shot learning, Text Generation with Prompting

Alternate Reality ⭐ 6

Recurrent Neural Networks will allow me to sample new text (essays, poems, emails) that I would have hypothetically written in New York given my four years of corpus literature as training data

TCube generates rich and fluent narratives that describes the characteristics, trends, and anomalies of any time-series data (domain-agnostic) using the transfer learning capabilities of PLMs.

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