https://github.com/kaifcoder/Stan

Develop and deploy a Large Language Model (LLM) based tool for generating human like responses to natural language inputs for network not connected over internet
https://github.com/kaifcoder/Stan

chroma huggingface-transformers langchain-python llm python streamlit

Last synced: 3 days ago
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Develop and deploy a Large Language Model (LLM) based tool for generating human like responses to natural language inputs for network not connected over internet

• Host: GitHub
• URL: https://github.com/kaifcoder/Stan
• Owner: kaifcoder
• Created: 2023-09-27T04:09:35.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-27T07:12:44.000Z (over 1 year ago)
• Last Synced: 2023-09-27T14:46:11.276Z (over 1 year ago)
• Topics: chroma, huggingface-transformers, langchain-python, llm, python, streamlit
• Language: Python
• Homepage:
• Size: 288 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# STAN - Text Analysis Tool

Stan is a powerful text analysis tool designed to summarize content and answer questions using large language models.

# Demo Video

https://github.com/kaifcoder/Stan/assets/57701861/40d051ed-a659-42c0-8f15-bef37f1b158e

## Key Features

- Summarize long texts into concise paragraphs.

- Answer questions about your text, such as 'What,' 'When,' and 'Who' questions.

- Works offline, ensuring data privacy and security.

- User-friendly interface for easy text analysis.

## How Stan Works

Stan is built upon the latest advancements in natural language processing. It utilizes a locally deployed language model to perform tasks such as summarization and question answering.

## Contact Information

For questions and support, please contact us at [contact@kaifcoder](mailto:[email protected]).

## Team

Stan is developed and maintained by a team of dedicated software engineers and AI enthusiasts.

## Privacy

We value your privacy. Stan does not require an internet connection and does not store your data.

## Acknowledgments

We would like to acknowledge the open-source community and the developers of the underlying libraries and tools that made Stan possible.