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@@ -19,7 +19,7 @@ keywords:
- embeddings
- ONNX Runtime
- quantized embedding model
category: ecosystem
category: demos-and-tutorials
---
Data Science and Machine Learning practitioners often find themselves navigating through a labyrinth of models, libraries, and frameworks. Which model to choose, what embedding size, and how to approach tokenizing, are just some questions you are faced with when starting your work. We understood how many data scientists wanted an easier and more intuitive means to do their embedding work. This is why we built FastEmbed, a Python library engineered for speed, efficiency, and usability. We have created easy to use default workflows, handling the 80% use cases in NLP embedding.