GPT-2 Model for Leetcode Questions in python

Overview

Leetcode using AI 🤖

GPT-2 Model for Leetcode Questions in python New demo here: https://huggingface.co/spaces/gagan3012/project-code-py

Note: the Answers might not make sense in some cases because of the bias in GPT-2 Current accuracy is capped at 90%.

Contribtuions: If you would like to make the model/UI better contributions (Issues/PRs) are welcome Check out CONTRIBUTIONS

How I built this : Linkedin

📢 Favour:

It would be highly motivating, if you can STAR this repo if you find it helpful. New improvements incoming!

Model

Two models have been developed for different use cases and they can be found at https://huggingface.co/gagan3012

The model weights can be found here: GPT-2 and DistilGPT-2

The model has been trained using Weights and Biases (Wandb) and PyTorch

GPT Neo model: https://huggingface.co/gagan3012/project-code-py-neo

Example usage:

from transformers import AutoTokenizer, AutoModelWithLMHead

tokenizer = AutoTokenizer.from_pretrained("gagan3012/project-code-py")

model = AutoModelWithLMHead.from_pretrained("gagan3012/project-code-py")

Demo

Streamlit App

A streamlit webapp has been setup to use the model: https://share.streamlit.io/gagan3012/project-code-py/app.py

image

Please create an issue in this repo if the demo is not working

Example results:

Question:

Write a function to delete a node in a singly-linked list. You will not be given access to the head of the list, instead you will be given access to the node to be deleted directly. It is guaranteed that the node to be deleted is not a tail node in the list.

Answer:

2->3 b = 3->1->2 t = ListNode(-1, 1) Note: The lexicographic ordering of the nodes in a tree matters. Do not assign values to nodes in a tree. Example 1: Input: [1,2,3] Output: 1->2->5 Explanation: 1->2->3->3->4, then 1->2->5[2] and then 5->1->3->4. Note: The length of a linked list will be in the range [1, 1000]. Node.val must be a valid LinkedListNode type. Both the length and the value of the nodes in a linked list will be in the range [-1000, 1000]. All nodes are distinct. """ # Definition for singly-linked list. # class ListNode: # def __init__(self, x): # self.val = x # self.next = None class Solution: def deleteNode(self, head: ListNode, val: int) -> None: """ BFS Linked List :param head: ListNode :param val: int :return: ListNode """ if head is not None: return head dummy = ListNode(-1, 1) dummy.next = head dummy.next.val = val dummy.next.next = head dummy.val = "" s1 = Solution() print(s1.deleteNode(head)) print(s1.deleteNode(-1)) print(s1.deleteNode(-1)) ">
""" Write a function to delete a node in a singly-linked list. You will not be given access to the head of the list, instead you will be given access to the node to be deleted directly. It is guaranteed that the node to be deleted is not a tail node in the list.

For example,
a = 1->2->3
b = 3->1->2
t = ListNode(-1, 1)

Note: The lexicographic ordering of the nodes in a tree matters. Do not assign values to nodes in a tree.
Example 1:

Input: [1,2,3]
Output: 1->2->5
Explanation: 1->2->3->3->4, then 1->2->5[2] and then 5->1->3->4.


Note:

The length of a linked list will be in the range [1, 1000].
Node.val must be a valid LinkedListNode type.
Both the length and the value of the nodes in a linked list will be in the range [-1000, 1000].
All nodes are distinct.
"""
# Definition for singly-linked list.
# class ListNode:
#     def __init__(self, x):
#         self.val = x
#         self.next = None

class Solution:
    def deleteNode(self, head: ListNode, val: int) -> None:
        """
        BFS
        Linked List
        :param head: ListNode
        :param val: int
        :return: ListNode
        """
        if head is not None:
            return head
        dummy = ListNode(-1, 1)
        dummy.next = head
        dummy.next.val = val
        dummy.next.next = head
        dummy.val = ""


s1 = Solution()
print(s1.deleteNode(head))
print(s1.deleteNode(-1))
print(s1.deleteNode(-1))
Owner
Gagan Bhatia
Software Developer | Machine Learning Enthusiast
Gagan Bhatia
Modular and extensible speech recognition library leveraging pytorch-lightning and hydra.

Lightning ASR Modular and extensible speech recognition library leveraging pytorch-lightning and hydra What is Lightning ASR • Installation • Get Star

Soohwan Kim 40 Sep 19, 2022
MiCECo - Misskey Custom Emoji Counter

MiCECo Misskey Custom Emoji Counter Introduction This little script counts custo

7 Dec 25, 2022
Sequence modeling benchmarks and temporal convolutional networks

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

CMU Locus Lab 3.5k Jan 03, 2023
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation

CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener

fastNLP 342 Jan 05, 2023
Healthsea is a spaCy pipeline for analyzing user reviews of supplementary products for their effects on health.

Welcome to Healthsea ✨ Create better access to health with spaCy. Healthsea is a pipeline for analyzing user reviews to supplement products by extract

Explosion 75 Dec 19, 2022
Must-read papers on improving efficiency for pre-trained language models.

Must-read papers on improving efficiency for pre-trained language models.

Tobias Lee 89 Jan 03, 2023
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents

BROS (BERT Relying On Spatiality) is a pre-trained language model focusing on text and layout for better key information extraction from documents. Given the OCR results of the document image, which

Clova AI Research 94 Dec 30, 2022
SimpleChinese2 集成了许多基本的中文NLP功能,使基于 Python 的中文文字处理和信息提取变得简单方便。

SimpleChinese2 SimpleChinese2 集成了许多基本的中文NLP功能,使基于 Python 的中文文字处理和信息提取变得简单方便。 声明 本项目是为方便个人工作所创建的,仅有部分代码原创。

Ming 30 Dec 02, 2022
Image2pcl - Enter the metaverse with 2D image to 3D projections

Image2PCL Enter the metaverse with 2D image to 3D projections! This is an implem

Benjamin Ho 0 Feb 05, 2022
Sequence-to-Sequence Framework in PyTorch

nmtpytorch allows training of various end-to-end neural architectures including but not limited to neural machine translation, image captioning and au

LIUM 395 Nov 21, 2022
Machine learning models from Singapore's NLP research community

SG-NLP Machine learning models from Singapore's natural language processing (NLP) research community. sgnlp is a Python package that allows you to eas

AI Singapore | AI Makerspace 21 Dec 17, 2022
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)

KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions

Kakao Brain 797 Dec 26, 2022
🧪 Cutting-edge experimental spaCy components and features

spacy-experimental: Cutting-edge experimental spaCy components and features This package includes experimental components and features for spaCy v3.x,

Explosion 65 Dec 30, 2022
String Gen + Word Checker

Creates random strings and checks if any of them are a real words. Mostly a waste of time ngl but it is cool to see it work and the fact that it can generate a real random word within10sec

1 Jan 06, 2022
ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab

AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode

Alibaba 1.4k Jan 04, 2023
GCRC: A Gaokao Chinese Reading Comprehension dataset for interpretable Evaluation

GCRC GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Eva

Yunxiao Zhao 5 Nov 04, 2022
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

303 Dec 17, 2022
Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统

Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统

wangle 823 Dec 28, 2022
Python interface for converting Penn Treebank trees to Stanford Dependencies and Universal Depenencies

PyStanfordDependencies Python interface for converting Penn Treebank trees to Universal Dependencies and Stanford Dependencies. Example usage Start by

David McClosky 64 May 08, 2022
GVT is a generic translation tool for parts of text on the PC screen with Text to Speak functionality.

GVT is a generic translation tool for parts of text on the PC screen with Text to Speech functionality. I wanted to create it because the existing tools that I experimented with did not satisfy me in

Nuked 1 Aug 21, 2022