https://github.com/bramvanroy/bert-for-inference

A small repo showing how to easily use BERT (or other transformers) for inference

https://github.com/bramvanroy/bert-for-inference

Science Score: 26.0%

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    Low similarity (7.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

A small repo showing how to easily use BERT (or other transformers) for inference

Basic Info
  • Host: GitHub
  • Owner: BramVanroy
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 182 KB
Statistics
  • Stars: 99
  • Watchers: 3
  • Forks: 21
  • Open Issues: 1
  • Releases: 0
Created over 6 years ago · Last pushed over 6 years ago
Metadata Files
Readme

README.md

Contents

Introduction to inference with BERT

introduction-to-bert.ipynb

Gives an introduction on how to use BERT for inference. Ideal if you want to use BERT for feature extraction.

Predicting stuff with masks

mask-probability.ipynb

Under construction. Code works but needs comments and more explanation.

Try notebooks online with binder

Binder

Local installation

  1. Clone from GitHub
  2. pipenv install inside the cloned directory (where the Pipfile is)
  3. Install the correct torch version for your system. You don't need torchvision. When using pipenv, you'll first have to activate shell and then install torch.

bash pipenv shell python -m pip install torch===1.3.1 -f https://download.pytorch.org/whl/torch_stable.html

To run the notebook, simply launch your jupyter notebook, e.g.

bash pipenv run jupyter notebook

Owner

  • Name: Bram Vanroy
  • Login: BramVanroy
  • Kind: user
  • Location: Belgium
  • Company: @CCL-KULeuven @instituutnederlandsetaal

👋 My name is Bram and I work on natural language processing and machine translation (evaluation) but I also spend a lot of time in this open-source world 🌍

GitHub Events

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Last Year

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Last synced: about 1 year ago

All Time
  • Total issues: 1
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 10 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
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  • monk1337 (1)
Pull Request Authors
  • GillesJ (1)
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