hs-math-nlp | Analysing Mathematical Reasoning Abilities of Neural Models

by andrewschreiber Jupyter Notebook Version: 2 License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | hs-math-nlp Summary

hs-math-nlp is a Jupyter Notebook library. hs-math-nlp has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Reproduction of 'Analysing Mathematical Reasoning Abilities of Neural Models' Saxton et. al. 2019

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Support

hs-math-nlp has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 0 have been closed. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of hs-math-nlp is 2

Quality

hs-math-nlp has no bugs reported.

Security

hs-math-nlp has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

hs-math-nlp does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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hs-math-nlp releases are available to install and integrate.

Installation instructions are available. Examples and code snippets are not available.

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hs-math-nlp Key Features

No Key Features are available at this moment for hs-math-nlp.

hs-math-nlp Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install hs-math-nlp

Set up a Python 3.7 environment. Enter the repo folder and run pip install -r requirements.txt. Optional: download the full 2GB dataset (https://console.cloud.google.com/storage/browser/_details/mathematics-dataset/mathematics_dataset-v1.0.tar.gz) and unzip in the project root directory.
Clone the repo
Set up a Python 3.7 environment
Enter the repo folder and run pip install -r requirements.txt
Optional: download the full 2GB dataset (https://console.cloud.google.com/storage/browser/_details/mathematics-dataset/mathematics_dataset-v1.0.tar.gz) and unzip in the project root directory.

Support

Arxiv paper: https://arxiv.org/abs/1904.01557ICLR 2019 Open Review: https://openreview.net/forum?id=H1gR5iR5FXDataset Code from paper: https://github.com/deepmind/mathematics_datasetPyTorch helpers: https://github.com/mandubian/pytorch_math_dataset

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