metadata
tags:
- model_hub_mixin
- pytorch_model_hub_mixin
license: wtfpl
datasets:
- jakartaresearch/cerpen-corpus
language:
- id
base_model:
- LocalWisdom/PurpleBoW
pipeline_tag: feature-extraction
PurpleCBoW
A very simple implementation of Continuous Bag-of-Words for those learning about Natural Language Processing.
What's The Difference With Skip-Gram and Word2Vec?
Well, Word2Vec is the concept of using a shallow neural network to turn a word into vector. Meanwhile, Skip-Gram is just another variant of CBOW. Skip-Gram and CBOW is Word2Vec.
Usage
Download the train.ipynb file and execute every cell.
At the bottom of the notebook, we have the "inference" part where we can test with whatever word is in the model vocabulary.