Lamini provides LLM inference and tuning for enterprises, offering factual LLMs that can be deployed anywhere in 10 minutes.

Lamini

Lamini makes it possible for enterprises to turn proprietary data into the next generation of LLM capabilities, by offering a platform for in-house software teams to uplevel to OpenAI-level AI teams and to build within the security of their existing infrastructure.

Get ready for GPU-agnostic scaling with Lamini! *Zero* code changes to run/tune LLMs on NVIDIA & AMD GPUs.

Learn how 1M adapters are optimized on NVIDIA GPUs for Memory Tuning!

✍️ with NVIDIA AI: https://lnkd.in/giNCGp4a

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Excited for Lamini to be a finalist for the annual VentureBeat AI Innovations Awards! 

The whole team has been working hard on setting a new accuracy standard for LLMs, so it’s possible for dev teams to build highly factual LLMs and agents.

Come chat with us if you think this could be helpful: https://lnkd.in/gcBr9XnK

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Excited to share that Lamini is partnering with Meta 🤝 to bring you code recipes for finetuning factual LLMs & agentic workflows 🎉

Recipe #1: How to Memory Tune Llama-3 into a SQL agent for your precise schema: 30% -> 95% accuracy.

Blog 👉 https://lnkd.in/gq_WVrei 
Code👇🏻

One of our amazing engineers—Jonathan Li—put together an open-source Memory Tuning recipe for an LLM agent. 

Step through how you can iteratively build this agent to precisely generate SQL (30% -> 95% accuracy) on an open-source SQL database of NBA players & teams.

Run it on Meta's Llama Recipes 👩🏻‍💻 https://lnkd.in/gYP84Umh

Run it in Colab 🧑🏽‍💻 https://lnkd.in/gPGDaySu

Ping us to Memory Tune on your own schema, or other LLM / agent use case 👉 https://lnkd.in/gcBr9XnK

Over 1500 of our colleagues joined me and the team for an exclusive Learning and Development session with Sharon Zhou, PhD, CEO and co-founder of Lamini, a startup offering state-of-the-art LLM inference and tuning capabilites for enterprises. 

We covered many interesting topics, including key technical considerations when deploying LLMs at scale, cost and other implications of such deployments and how to build effective Generative AI teams to deliver new products and services. 

Miriam Silver, CFA Sharon Zhou, PhD Danielle Gershon Nimrod Barak

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