Open LLM Search
| Property | Value |
|---|---|
| Base Model | Llama-2-7b-32k |
| License | Llama 2 |
| Language | English |
| Framework | PyTorch |
What is open-llm-search?
Open LLM Search is an innovative adaptation of Together AI's llama-2-7b-32k model, specifically designed to address the growing need for large language models with direct internet search capabilities. Unlike proprietary solutions from major tech companies, this model offers search functionality without data logging concerns. Despite its relatively modest 7 billion parameters, the model leverages fine-tuned capabilities and an expanded context window to excel in information extraction from web pages.
Implementation Details
The model employs a sophisticated fine-tuning process that utilizes both GPT-4 and GPT-4-32k for synthetic data generation. The training pipeline involves generating queries, fetching website results, content extraction, and multi-stage summarization to create comprehensive training data.
- Query generation and website content extraction workflow
- Multi-stage summarization using GPT-4 models
- Structured input format with instructions, user, and assistant roles
- Extended context window for handling large text chunks
Core Capabilities
- Direct web page information extraction
- Privacy-focused search functionality
- Enhanced context processing
- Efficient summarization of multiple sources
- Structured response generation
Frequently Asked Questions
Q: What makes this model unique?
The model's unique strength lies in its ability to perform web searches without data logging, combined with its efficient 7B parameter architecture and extended context window. This makes it a privacy-conscious alternative to proprietary solutions while maintaining high performance in search tasks.
Q: What are the recommended use cases?
The model is ideal for applications requiring web information extraction, content summarization, and search-based question answering. It's particularly suitable for developers and organizations seeking an open-source solution for search capabilities without privacy concerns.
