Petro Milan

[Full Workshop] Llama 3 at 1,000 tok/s on the SambaNova AI Platform

Feb 7, 2025 · 1:00:58

Michelle Matern and Petro Milan of SambaNova present their full-stack AI platform, built on the SN40L RDU chip with a three-tiered memory architecture capable of storing up to 5 trillion parameters. They demonstrate Samba1 Composition of Experts (CoE), a trillion-parameter model combining 92 expert models behind a single endpoint, and show Llama-3-8B achieving 1,000 tokens per second with a time-to-first-token of 0.09 seconds and total inference time of 0.65 seconds—far exceeding GPU-based providers. The workshop includes a hands-on basic inference call using LangChain and SambaStudio API, and a RAG-based Q&A system for enterprise search that integrates Unstructured for document loading, E5-large-v2 embeddings, ChromaDB vector store, and the high-speed Llama-3 endpoint. Attendees learn to configure prompts with special Llama-3 tags, set chunk size and overlap, and optionally run embeddings on SambaNova's RDU hardware for faster processing.

Build enterprise generative AI apps using Llama 3 at 1,000 tokens/s on the SambaNova AI platform

Sep 11, 2024 · 54:34

SambaNova’s Michelle Matern and Petro Milan present their full-stack AI platform, demonstrating how the SN40L RDU chip enables Llama 3 inference at 1,000 tokens per second. They introduce Samba-1, a composition of 92 expert models behind a single endpoint, and benchmark it against GPT-3.5 and GPT-4 on enterprise tasks like information extraction and text-to-SQL. The workshop then builds a RAG-based Q&A system using LangChain, Unstructured, E5-large-v2 embeddings, ChromaDB, and Llama-3-8B-Instruct at 1,000 tokens per second. Attendees set up the environment, load documents, and run inference with real-time metrics showing time to first token of 0.09 seconds and total inference time of 0.65 seconds.