https://github.com/ototot/doc2vecc

GPU accelerated implementation for Doc2VecC
https://github.com/ototot/doc2vecc

doc2vec doc2vecc word-embedding word-embeddings

Last synced: 4 days ago
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GPU accelerated implementation for Doc2VecC

• Host: GitHub
• URL: https://github.com/ototot/doc2vecc
• Owner: oToToT
• License: apache-2.0
• Created: 2020-05-20T20:52:36.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2021-02-05T04:34:32.000Z (almost 4 years ago)
• Last Synced: 2024-11-01T12:42:04.379Z (about 2 months ago)
• Topics: doc2vec, doc2vecc, word-embedding, word-embeddings
• Language: Cuda
• Homepage:
• Size: 329 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# **The implementation in this repo is totally wrong, do NOT use this repo** #

# Doc2VecC #

GPU accelerated implementation of [Efficient Vector Representation for Documents Through Corruption](https://openreview.net/pdf?id=B1Igu2ogg)

## Acknowledge ##

The original implementaion is from [@mchen24/iclr2017](https://github.com/mchen24/iclr2017).  

This repository only accelerate the training progress while **NOT** including the whole experiment.

You should check the original implementation for more detail.

## Getting started ##

### Building this Project ###

```bash

git clone https://github.com/oToToT/Doc2VecC

cd Doc2VecC/build

cmake -DCMAKE_BUILD_TYPE=Release .. && cmake --build .

```

### Usage ###

```bash

./doc2vecc

```

## Reference ##

If you found this code useful, please cite the following paper:

Minmin Chen. **"Efficient Vector Representation for Documents Through Corruption."** *5th International Conference on Learning Representations, ICLR (2017).*

```

@article{chen2017efficient,

  title={Efficient Vector Representation for Documents Through Corruption},

  author={Chen, Minmin},

  journal={5th International Conference on Learning Representations},

  year={2017}

}

```

## License ##

[Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0)