In today’s data-driven world, effective document management and analysis are crucial across various industries. Our innovative LLM-Based Document Analyzer Cloud Application aims to streamline this process by utilizing advanced machine learning techniques to rank and analyze documents based on user queries.
Project Overview:
This project uses the power of Large Language Models (LLMs) and various machine learning frameworks to provide a robust cloud application capable of processing documents in real-time. By leveraging Supercomputing as a Service, our platform ensures high-performance execution, delivering fast and accurate results to users.
Key Features:
- Real-time Document Analysis: Analyze documents as per user-defined queries.
- Ranking Mechanism: Rank documents based on their relevance to specific queries.
- Scalability: Utilize PakSupercomputing's HPC resources for efficient computation.
Technology Stack
To achieve our goals, we employ a diverse technology stack that includes:
- Core Models:
- Basic to advanced LLMs
- N-Gram Models
- FeedForward Networks (FFNs)
- Recurrent Neural Networks (RNNs)
- Long Short-Term Memory (LSTMs)
- Gated Recurrent Units (GRUs)
- Llama2 Transformer for cutting-edge performance
- Framework: PyTorch
- Supercomputing: PakSupercomputing HPC for high-performance execution
- Cloud Platform: Deployed using cloud architecture for scalable access and fast query responses.
Applications:
The LLM-Based Document Analyzer has a wide array of applications, including:
1. HR & Recruitment
Automatically rank CVs based on job requirements and custom queries, streamlining the recruitment process.
2. Book and Article Ranking
Analyze and rank books, articles, or papers based on user-defined criteria, enhancing research and content discovery.
3. Legal Document Analysis
Assist in finding relevant case law, contracts, or legal precedents based on key phrases or legal requirements.
4. Academic Research
Help researchers quickly identify relevant papers, theses, or publications that match specific topics or hypotheses.
5. Market Research
Analyze and rank reports, product reviews, or surveys based on trends, consumer feedback, or specific market segments.
6. General Document Management
Efficiently manage and analyze large datasets, reports, or archives by categorizing and ranking them based on specified queries.
http://119.156.30.83:8502/
Collaborators: PakSupercomputing
Unal Center of Educaiton Research & Development
