FAQ from Lamini
What is Lamini?
Lamini is an AI-powered LLM platform designed for enterprise software development, enabling developers to automate workflows, streamline processes, and boost productivity with generative AI and machine learning.
How to use Lamini?
To use Lamini, follow these steps: 1. Sign up for a Lamini account. 2. Connect your enterprise data warehouse to the Lamini platform. 3. Use Lamini's Python library, REST APIs, or user interfaces to train, evaluate, and deploy private models. 4. Automate and optimize development processes with Lamini's AI. 5. Maintain data privacy and security by deploying models on-premise or in your VPC.
What makes Lamini different from other AI platforms?
Lamini stands out due to: 1. Data Privacy: Use your private data in a secure environment. 2. Ownership and Flexibility: Own and control your LLMs, with the ability to switch models as needed. 3. Cost and Performance Control: Customize model cost, latency, and throughput to meet your team's requirements.
What does the LLM platform do?
The LLM platform optimizes LLMs using state-of-the-art technologies and research, including fine-tuning, RLHF, retrieval-augmented training, data augmentation, and GPU optimization, leveraging models like GPT-3 and ChatGPT for top performance.
What LLMs does Lamini use?
Lamini utilizes the latest generation of models from sources like HuggingFace and OpenAI. The choice of models is tailored to the specific needs and data constraints of each customer, ensuring optimal results.
Can I export and run the model myself?
Yes, you can deploy the LLM to any cloud service or on-premise environment, including setting up scaled inference for your infrastructure. You can export the model weights and host the LLM yourself.
How much does it cost to use Lamini?
Lamini offers a free tier for training small LLMs. For enterprise pricing details, please refer to our contact page. Enterprise customers can download model weights without limitations on size and type, with full control over throughput and latency.