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Fine-tuningPaidOpen Source
LAMINI
Fine-tune and deploy LLMs with memory tuning
Apache-2.0
ABOUT
Fine-tuning and deploying LLMs for enterprise use cases requires managing infrastructure, data pipelines, experiment tracking, and model serving — a complex orchestration problem that most teams don't have the resources to build from scratch. Lamini provides a managed platform and Python SDK that handles the full lifecycle: data preparation, fine-tuning with memory tuning and RLHF, evaluation, and deployment via a simple API. Teams can start with a single pip install and scale to production without managing GPU clusters.
INSTALL
pip install laminiINTEGRATION GUIDE
1. Fine-tune open-source LLMs on proprietary enterprise data with memory tuning for reduced hallucination
2. Build RLHF pipelines that collect human preferences and optimize model behavior through reinforcement learning
3. Deploy customized LLMs behind a managed API endpoint with automatic scaling and monitoring
4. Evaluate fine-tuned models against baseline metrics using built-in evaluation harnesses
5. Iterate on model quality with experiment tracking, data versioning, and A/B comparison dashboards
TAGS
pythonfine-tuningllmsdkmemory-tuningrlhfenterprise