5, 10 or 20 seats+ for your team - learn more
Your local school district has a basic LLM chatbot based on Llama—now it needs fine-tuning! That’s where you come in. In this liveProject, you’ll utilize the Supervised Fine Tuning (SFT) approach to customize a chemistry chatbot for teaching children. SFT uses question-and-answer pairs to train a model to answer questions with a given answer. To achieve this, you will need to prepare your training data, utilizellama.cpp tools for LORA fine-tuning, and CLI tools to test inference on a fine-tuned model.
This liveProject is for software developers and IT professionals who are interested in building LLM applications in their own domains. To begin this liveProject, you will need to know the following:
geekle is based on a wordle clone.