Unity ML-Agents | Pretrain an LLM from Scratch with Sentence Transformers | Part 20c
0*Welcome back to our Tau LLM series! ๐*
In this episode, we're excited to continue our journey with some significant updates and improvements:
**Oproof Integration Success**: We've successfully integrated the oproof Python package into our system. This package validates prompt-response pairs using Ollama and Python, ensuring data integrity and accuracy.
**Enhanced Command Processor**: Our command processor now handles lists of arguments instead of just a single string, making it more versatile and powerful.
**Debugging and Fine-Tuning**: Although our oproof engine is working, the proof task isn't processing the returned data correctly. We'll be debugging and fine-tuning this to ensure everything runs smoothly.
**Output Verification**: We'll inspect the output to verify that the proof engine is working as expected and make necessary adjustments.
Join us as we tackle these challenges and enhance our LLM with custom tools and techniques. Whether you're a beginner or an experienced developer, this episode offers valuable insights into developing, testing, and refining an LLM.
Stay tuned and let's get started! ๐