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@sanjayaksaxena sanjayaksaxena released this 24 Mar 09:05
· 25 commits to master since this release
2.0.0
9425728

Version 2.0.0 March 24, 2024

✨ Features

  • Seamless word embedding integration enhances winkNLP's semantic capabilities. 🎉 👏 🙌
  • Pre-trained 100-dimensional word embeddings for over 350,000 English words released: wink-embeddings-sg-100d. 💯
  • API remains unchanged — no code updates needed for existing projects. The new APIs include: 🤩
    • Obtain vector for a token: Use the .vectorOf( token ) API.
    • Compute sentence/document embeddings: Employ the as.vector helper: use .out( its.lemma, as.vector ) on tokens of a sentence or document. You can also use its.value or its.normal. Tokens can be pre-processed to remove stop words etc using the .filter() API. Note, the as.vector helper uses averaging technique.
    • Generate contextual vectors: Leverage the .contextualVectors() method on a document. Useful for pure browser-side applications! Generate custom vectors contextually relevant to your corpus and use them in place of larger pre-trained wink embeddings.
  • Comprehensive documentation along with interesting examples is coming up shortly. Stay tuned for updates! 😎
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