Paper to Code automates the incorporation of research paper concepts into practical code using OpenAI's GPT models, bridging theory and implementation.
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Updated
Jan 10, 2024 - Python
Paper to Code automates the incorporation of research paper concepts into practical code using OpenAI's GPT models, bridging theory and implementation.
BabyGPT: Build Your Own GPT Large Language Model from Scratch Pre-Training Generative Transformer Models: Building GPT from Scratch with a Step-by-Step Guide to Generative AI in PyTorch and Python
Code for the paper "On the Expressivity Role of LayerNorm in Transformers' Attention" (Findings of ACL'2023)
The open source code for the paper "Block Attention and Switchable Normalization based Deep Learning Framework for Segmentation of Retinal Vessels"
RNNs with layer normalization; Prep package for tensorflow/addons, see v0.8.2, and commit https://github.com/tensorflow/addons/commit/cdb43ffd7e4b89d6ce8cdadcd62fec46c7f0f7fa
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Layer normalization with einops semantics.
Analysis of different types of common Normalization schemes in Deep Learning
Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
Time-Sensitive Deep Learning for ICU Outcome Prediction Without Variable Selection or Cleaning.
Layer normalization in PyTorch
PyTorch implementation of Neural Turing Machine recurrent neural network
The extension of torch.nn.LSTMCell
The implementation of Layer Normalization which follows paper "https://arxiv.org/abs/1607.06450".
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Fast-Slow Recurrent Neural Networks
TensorFlow implementation of normalizations such as Layer Normalization, HyperNetworks.
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