code-kern-ai/embedders
With embedders, you can easily convert your texts into sentence- or token-level embeddings within a few lines of code. Use cases for this include similarity search between texts, information extraction such as named entity recognition, or basic text classification.
This tool helps data scientists and ML engineers transform raw text into numerical representations called embeddings. You input text like sentences or entire documents, and it outputs lists of numbers that capture the meaning or context of the text. These embeddings are crucial for tasks like finding similar texts, extracting specific information, or categorizing documents.
No commits in the last 6 months. Available on PyPI.
Use this if you need to convert text data into a numerical format suitable for machine learning models, especially for tasks involving text similarity, information extraction, or classification.
Not ideal if you are looking for a ready-to-use application or a no-code solution for text analysis, as this requires coding knowledge to implement.
Stars
21
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 14, 2025
Commits (30d)
0
Dependencies
9
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