How To Train Your LLM 🐉

​🚨Looking for a venue, please reach out!🚨

​A hands-on beginner workshop on what actually happens inside an LLM.

​You’ve used ChatGPT. Maybe you’ve played with prompts, APIs or open models.

​But what does it actually mean to train a language model?

​In this 4-hour workshop, we’ll go from a tiny model that barely knows how to speak to a real pretrained LLM that we can fine-tune ourselves.

​No AI magic. No 80-slide lecture. We’ll actually build things.

​What we’ll do

• ​Turn text into tokens and see how next-token prediction works

• ​Train a tiny language model from scratch

• ​See how a Transformer improves on our first model

• ​Experiment with temperature, training time and model size

• ​Run a real open-source LLM on a GPU

• ​Understand CPU vs. GPU, memory and quantization

• ​Fine-tune a pretrained LLM with LoRA

• ​Compare the model before and after training

​You’ll leave understanding

​Training vs. inference. Pretraining vs. fine-tuning. Tokens, parameters, Transformers, GPUs, LoRA and why any of it matters.

​More importantly, you’ll have actually used these concepts yourself instead of just hearing about them.

​Who is this for?

​Developers, students, data/product people and technically curious humans who want to understand LLMs beyond prompting.

​You don’t need previous machine-learning experience.

​Basic Python familiarity will help, but the exercises are guided.

​Format

​4 hours · Beginner-friendly · Hands-on

​We’ll use a prepared cloud environment with access to GPUs, so you won’t need to install CUDA, own a powerful laptop or spend half the workshop debugging dependencies.

​Bring your laptop and curiosity.

​🚨We're looking for a venue to host this. Please contact Sonya on LinkedIn.🚨