Dave Hillman
figuring things out...
Some things to think about...
Big things may look big, but little things often matter more.
Work smarter, not harder!
It's always darkest before it goes pitch black.
Located under the clear blue skys of North Carolina.
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Personal Projects...
< Localized LLMs (L3M) >
Localized Large Language Models (LLMs or L3Ms) are computational models that mimic how text is understood and used to simulate human intelligence.
Identify and evaluate LLMs for definitions, categorization, and summarization...running on localized CPU-based architectures.
ChatGPT and cloud-based LLMs are hardware resource intensive. Running LLMs on local machines means you're not subject to being connected all the time, have more privacy, and have the flexibility to change models as they improve.
Capabilities include responding to questions, categorization, document summarization, keyword (general, name, place) extraction, definition generator, outputting to JSON.
Current Focus: optimization...making it faster and more efficient.
Technologies used
- LLMs
- Python
- LLM Support Libraries
- Web Stack
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< Enhanced Entity Attribute Value (EEAV) >
EEAV is a very flexible model for capturing and exploiting data sets.
EEAV focuses on data-driven application development.
Starting with a table of data (CSV, JSON), ingest it, then manipulate it for a variety of pruposes. Any 2-dimensional data set can be captured in 3 tables: dataset, attributes, and values.
A secondary aspect of this effort is a web-based environment that makes it easily accessible and available.
Current Focus: adding additional features to the REST capability.
Technologies used
- Python
- Web Stack
- Postgres, SQLite
- JavaScript, HTML, CSS
- Tabulator (table viewer)