Lamini - Enterprise LLM Platform for Finetuning

Your data.
Your infra.
Your LLM.

Lamini is the LLM platform for enterprises and developers to build customized, private models: easier, faster, and higher-performing than any general LLMs.

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Partnered with leading data companies

Lamini channel partner Databricks

Lamini channel partner Nutanix

Develop LLMs 100x faster

Save over 100 engineering hours per week:

Finetune in just minutes.
Chain 1000 different LLMs in milliseconds on 1 GPU.
Maximize accuracy with the latest AI research baked in,
without tuning 1000 knobs.

Lamini LLM Platform - Keep Complete Control

Keep Complete Control

Maintain complete data privacy and security. Deploy your custom models privately on premise, in your VPC, or easily portable across both.

Lamini LLM Platform - Easy UX for Every Developer

Easy UX for Every Developer

With just a few lines of code, our powerful yet simple Python library, REST APIs, and elegant user interfaces enable every developer to quickly train, evaluate, and deploy on Day 1. No ML expertise required.

Lamini LLM Platform - Full Self-Serve, Enterprise-Class Support

Full Self-Serve, Enterprise-Class Support

Our fully self-serve platform uplevels your entire engineering organization’s capabilities and makes it easy to train LLMs for thousands of use cases at a time. Enterprise customers receive unmatched support from our dedicated AI engineers to build the highest performing models that meet your product requirements

Try our finetuning demos!

Finetuning Your Custom LLM

Walk through our finetuning pipeline, so you can train custom models on your data.

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Question-Answer LLM Finetuning

This walkthrough goes through a basic question-answer LLM over your data.

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Llama V2 Parameter-Efficient Finetuning

Walk through Lamini's easy LlamaV2 runner using finetuning.

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Finetuned vs. Non-finetuned LLMs

Finetune a question-answer LLM over your data (Taylor Swift, BTS datasets!).

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Build your AI moat now.

Simple Pricing

Free

Finetuning only

Small model (~400M); < 250K tokens

Train on our servers; queued

Inference is 200 hits + $0.10/hit, variable QPS, no export weights

Base vs. Finetuned model evaluation

Enterprise

Advanced Optimizations (LoRA, PEFT, RLHF, model/data parallelism, sharding, etc.)

Any size model; 1T+ tokens

Train on your private infrastructure, or scale on ours; skip the queue

Inference is 1M hits, higher & more stableQPS, weights exportable

Full Evaluation Suite

How is this different than just using a single provider’s (e.g. OpenAI’s) APIs off the shelf?

3 major reasons from our customers:
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1. Data privacy: Use private data in your own secure environment. Use all of your data, rather than what fits into a prompt.
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2. Ownership & Flexibility: Own the LLM you train with your own engineering team, and flexibly swap out models as new ones appear each day. Build up AI know-how and an AI moat internally at your company, while getting a big infrastructure lift.
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3. Control (cost, latency, throughput): With ownership, you also have more control over the (much lower) cost and (much lower) latency of the model. We expose these controls in an easy interface for your engineering team to customize.

What does the LLM platform do?

Our platform runs and optimizes your LLM.

It brings several of the latest technologies and research to bear that was able to make ChatGPT from GPT-3, as well as Github Copilot from Codex.

These include, among others, fine-tuning, RLHF, retrieval-augmented training, data augmentation, and GPU optimization.

What LLMs is the LLM platform using under the hood?

We build on the latest generation of models to make your LLM perform best, including any LLM on HuggingFace and OpenAI's models. We work with customers to determine which models are appropriate, depending on your specific use cases and data constraints.

For example, using OpenAI’s well-known GPT-3 and ChatGPT models are a great starting point for some customers, but not others. We believe in following your needs, and using the best models for you.

Do you build my own large model?

Yes, the resulting model is very large! It depends on what base model you select, or have us automatically select based on your data and use case.

However, what’s exciting is that it builds on the great work before it, such as GPT-3 or ChatGPT. These general purpose models know English and can answer in the general vicinity of your tasks.

We take it to the next level to teach it to understand your company’s language and specific use cases, by using your data.

This means it will do better than a general purpose model on tasks that matter to you, but it won’t be as good as a general purpose model on generic tasks without any data, e.g. putting together a grocery list (unless that’s what your company does).

If I want to export the model and run it myself, can I do that?

Yes, we deploy to any cloud service (e.g. VPC) and on premise.

This includes setup for running your LLM in your own environment for scaled inference.

If you want to, you can export the weights from our platform and host the LLM yourself.

How expensive is using your platform to build and use my model?

We have a free tier, where training a small LLM is free. You also get $20 free credits with each new account for inference.

Please see our contact page for our Enterprise tier, where you can download the model weights, and are not limited to model size, type, and can control throughput and latency.

Have other questions?