In this event, AI Makerspace breaks down the steps of ReFT, which consists of the warm-up stage and the reinforcement learning state. They will demonstrate how to code the core aspects of ReFT yourself in a Google Colab notebook environment, and all code will be provided directly to attendees!
Join AI Makerspace on Wednesday, Feb. 28, at 10 AM PT! For a workshop on DPO. Come learn how it differs from the techniques of RLHF and why all indications are showing it's rapidly becoming the new industry standard.
AI Makerspace presents part 2 of the Alignment series, Aligning LLMs: RLAIF! They will tackle RLAIF, a technique that attempts to solve the fundamental bottleneck of RLHF, namely, that it’s kind of expensive to collect a ton of data directly from humans!
AI Makerspace is hosting a deep dive into the OLMo series of models, including a discussion of the Dolma pre-training dataset as the model architectures leveraged for each of the three newly released versions: OLMo-1B, OLMo-7B, and OLMo-7B-Twin-2T!
Join AI Makerspace for a special event on RAG! Deep dive into the art of evaluating complex LLM applications that leverage Retrieval Augmented Generation (RAG), the technique that aims to ground the outputs of LLMs in fact-checkable information.
AI Makerspace is hosting a 4-part series on Aligning LLMs! In this first event on RLHF, they aim to give you some deep intuition into how models like InstructGPT and Llama 2 leveraged human feedback to align with us on what it means to be “helpful, honest, and harmless.”
Come and learn the basics of serving and inference of Large Language Models and how vLLM relieves memory bottlenecks that limit serving performance at scale!
Join AI Makerspace for a workshop on Quantization of LLMs and Fine-Tuning with QLoRA! Learn how to use quantization for loading, fine-tuning, and performing inference on LLMs!
Are you an AI Buisness leader looking to implement AI engineering and AI product management talent? Then, this workshop is for you! Join the AI Makerspace team Nov. 13 at 10 AM PST.
Join the AI Makerspace team for a workshop on Fine-Tuning 101: From LLMs to Embeddings! They'll demonstrate new capabilities that aspiring AI engineers should be adding to their tool belt.
Greg Loughnane and Chris Alexiuk will discuss how to use hierarchical embeddings to return relevant context from a large dataset, as measured by context precision and context recall via the RAG ASsessment framework, and also show the impact of fine-tuning the embedding model on retrieval metrics.