The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
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refinery-sample-projects reviews and mentions
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How to fine-tune your embeddings for better similarity search
This blog post will share our experience with fine-tuning sentence embeddings on a commonly available dataset using similarity learning. We additionally explore how this could benefit the labeling workflow in the Kern AI refinery. To understand this post, you should know what embeddings are and how they are generated. A rough idea of what fine-tuning is also helps. All the code and data referenced in this post is available on GitHub.
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Build your own stock sentiment classifier with Kern Refinery (video series)
Repository of the sample use case for the UI elements (optional).
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Show HN: If VS Code had a data-centric IDE sibling, what would that look like?
Hey, I'm Johannes - one of the maintainers of refinery. Thanks Jonathan for sharing!!
Would be super excited if you guys have any feedback. It's nowhere near perfect yet, but you can already use it to build some great data-centric use cases. Amongst others for sentiment analysis, conversational AI or finetuning of your embeddings (which you can check out here: https://github.com/code-kern-ai/refinery-sample-projects).
Let me know what you think :)
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A note from our sponsor - WorkOS
workos.com | 28 Mar 2024
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code-kern-ai/refinery-sample-projects is an open source project licensed under Apache License 2.0 which is an OSI approved license.