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Smartloop
Enterprise SLM Platform

What is Smartloop?

Smartloop is an open-source and no-code Small Language Model (SLM) platform designed for creating domain-specific agents. It allows businesses and large organizations to leverage their personal and sensitive data to build tailored AI solutions. The platform prioritizes data privacy and security by offering on-premise and private cloud deployments.

Smartloop offers a cost-effective and energy-efficient alternative to large language models. Its fine-tuning capabilities, using techniques like LoRA (Low Rank Adaption), enable the creation of highly accurate models for specialized tasks. The platform is fully managed and includes a web UI for easy document upload and interaction. Smartloop uses Llama 3 as its base model.

Features

  • Fine-tuning: Fine-tuning of models using private data.
  • Web UI: Use the web UI to upload documents and then interact with them collectively via the assistant.
  • Fully Managed: Fully managed platform as a service.
  • Cost-effective: Cost-effective solution tailored to your needs.
  • On-Premise/Private Cloud: Installation on edge or private cloud.
  • High-level API and Interface: High-level API and Interface available.

Use Cases

  • Creating domain-specific agents for specialized tasks.
  • Processing and analyzing sensitive data securely.
  • Streamlining existing processes with AI-powered assistants.
  • Building custom AI solutions without extensive coding knowledge.

FAQs

  • What is fine-tuning a model?
    The purpose of fine-tuning is to convert a model into a more specialized version for a given dataset. This enhances the model's accuracy for a specific topic or domain.
  • What is baseline models vs fine-tuned models?
    Baseline models like GPT-4 are well-suited for general-purpose reasoning, whereas fine-tuned models are primarily used to create domain-specific LLMs for more specialized applications.
  • How do you fine-tune models?
    We use different techniques but primarily use LoRA (Low Rank Adaption) to fine-tune models which makes it efficient in terms of memory, loading and un-loading of models.
  • What is your baseline model?
    We primarily use Llama 3 as our base model, allowing us to fine-tune it with private data in an on-premises setting

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