Glove 6B 100


GloVe (Global Vectors) is a model for distributed word representation. This is achieved by mapping words into a meaningful space where the distance between words is related to semantic similarity. It outperformed many common Word2vec models on the word analogy task. One benefit of GloVe is that it is the result of directly modeling relationships, instead of getting them as a side effect of training a language model.

Live Demo Open in Colab Download

How to use

embeddings = WordEmbeddingsModel.pretrained("glove_100d", "en") \
      .setInputCols("sentence", "token") \

val embeddings = WordEmbeddingsModel.pretrained("glove_100d", "en")
      .setInputCols("sentence", "token")

Model Information

Model Name: glove_100d
Type: word_embeddings
Compatibility: Spark NLP 2.4.0+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: [en]
Dimension: 100
Case sensitive: false

Data Source

The model is imported from