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https://github.com/chirayu-tripathi/paper-implementations

My implementation of Machine Learning and Deep Learning papers from scratch.

https://github.com/chirayu-tripathi/paper-implementations

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ✓
    Academic publication links
    Links to: arxiv.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.6%) to scientific vocabulary

Keywords

natural-language-processing research-paper-implementation transformers
Last synced: 5 months ago · JSON representation

Repository

My implementation of Machine Learning and Deep Learning papers from scratch.

Basic Info
  • Host: GitHub
  • Owner: Chirayu-Tripathi
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 112 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
natural-language-processing research-paper-implementation transformers
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

Paper-Implementations

My implementation of Machine Learning and Deep Learning papers from scratch.

| Paper Name | Link to Paper | Year Published | GitHub Folder | |------------|----------------|---------------|---------------| | Improving Language Understanding by Generative Pre-Training| GPT Paper | 2018 | GPT Implementation | | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | BERT Paper | 2019 | BERT Implementation | | Language Models are Unsupervised Multitask Learners | GPT2 Paper | 2019 | GPT2 Implementation | | LoRA: Low-Rank Adaptation of Large Language Models | LoRA Paper | 2021 | LoRA Implementation |

Some useful resources.

List of resources, that I found helpful while understanding and coding the concepts.

  1. Attention is all you need (Transformer) - Model explanation (including math), Inference and Training by Umar jamil: Youtube.

  2. Coding a Transformer from scratch on PyTorch, with full explanation, training and inference by Umar jamil: Youtube.

  3. Let's build GPT: from scratch, in code, spelled out by Andrej Karpathy. Youtube.

  4. Formal Algorithms for Transformers. arXiv

Owner

  • Name: Chirayu Tripathi
  • Login: Chirayu-Tripathi
  • Kind: user
  • Location: Gainesville, FL
  • Company: University of Florida, College of Medicine

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