Welcome to SuperAnnotate’s LLM toolbox! This custom editor is designed to cover a wide range of LLM use cases, providing top-notch data governance, security, customizability, data curation and many more. Try out diverse LLM experiments in just a few seconds without any complications, integrate the tool with your custom API and enjoy your LLM journey!
This repository is organized into three main use cases, described with their respective codes and interpretations. You may find instructions for each usage in their respective readme files. Below is an overview of the contents:
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Use Case 1: Chat rating
- Scale your language models experience by ranking both prompts and answers of your chat.
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Use Case 2: RLHF for image generation
- Generate images with any prompts for your use case, rate the best output, significantly improve your model’s performance as a result.
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Use Case 3: Model comparison
- Choose the model that best describes your case, rate the response and experience the most optimized outputs from language models.
A big note here! With the SuperAnnotate LLM toolbox, LLM engineers can define UI behavior right in the browser using Python, a departure from the traditional JavaScript methods. This shift leverages the prevalent Python expertise in the LLM community, making the development process smoother and more intuitive.