Simple Annotated implementation of GPT-NeoX in PyTorch

Last update: Dec 03, 2022

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Overview

Simple Annotated implementation of GPT-NeoX in PyTorch

This is a simpler implementation of GPT-NeoX in PyTorch. We have taken out several optimizations in GPT-NeoX for simplicity.

Annotated implementation

Sample usages

Owner

labml.ai

Tools to help deep learning researchers

GitHub Repository https://lit.labml.ai/github/labmlai/neox/tree/main/src/neox/__init__.py

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Simple Annotated implementation of GPT-NeoX in PyTorch

Related tags

Overview

Simple Annotated implementation of GPT-NeoX in PyTorch

Annotated implementation

Sample usages

Owner

labml.ai

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

Problem: Given a nepali news find the category of the news

Pytorch-Named-Entity-Recognition-with-BERT

AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems

Code for CVPR 2021 paper: Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning

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Create a machine learning model which will predict if the mortgage will be approved or not based on 5 variables

In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.

A collection of Korean Text Datasets ready to use using Tensorflow-Datasets.

Transformer Based Korean Sentence Spacing Corrector

This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding".

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