refinery-sample-projects VS rasa

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.

Repository of the sample use case for the UI elements (optional).

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 :)

Support Rasa on GitHub ⭐

It itself is not a GPT. It is a a framework of a framework project built on top of Rasa (https://github.com/RasaHQ/rasa) and Langchain which by default uses gpt3.5-turbo (change it in the .env file) or any foundation model you wish.

There was already a GitHub issue https://github.com/RasaHQ/rasa/issues/11084 but it seems like there was no solution provided.

Rasa - also an open source platform. You can use it to build chatbots that are more in line with customer service and sales. Reading that, it’s kind of a big yikes for people under this kind of job knowing you can automate a part of their job via a chatbot. I think they also have a Pro version which is an extension that has additional analytics and probably more security features. I probably will check out the Open source one first and maybe ask about what the Pro version is.

At the moment it can recognise the type of statements in the training data set [1] and transpile them to Python, Java or C++ using the mappings defined here [2].

This is very different from how Codex/Autopilot work as it is trained using an NLU framework [3] which is usually used for training chatbots.

[1]: https://github.com/Flex-lang/transpiler/tree/master/transpil...

[2]: https://github.com/Flex-lang/transpiler/tree/master/transpil...

[3]: https://github.com/RasaHQ/rasa

Check out Rasa

It looks like it is built upon a Chatbot platform called “messengerx.io”, which itself seems to be built upon an open-source/machine-learning framework for voice/text conversations called “Rasa”

Use Python and use the Rasa framework to make a chat bot. https://rasa.com/docs/

This example is sourced from RasaHQ