Swirl is open-source software that uses AI to simultaneously search multiple content and data sources, finds the best results using a reader LLM, then prompts Generative AI, enabling you to get answers from your own data.
HQQ is a fast and accurate model quantizer that skips the need for calibration data. It's super simple to implement (just a few lines of code for the optimizer). It can crunch through quantizing the Llama2-70B model in only 4 minutes!
Tips on improving your GitHub repository organization and structure. Bullet Points:
- Create meaningful branch names - Use descriptive commit messages - Keep a clean project history
- Separate your code into well-organized directories - Follow a consistent naming convention - Make use of pull requests
- Collaborate effectively by writing clear documentation - Maintain good communication within your team Keywords: GitHub, repository best practices, organization, structure, branch names, commit messages, project history, directories, naming conventions, pull requests, collaboration, documentation, effective communication
- Create meaningful branch names - Use descriptive commit messages - Keep a clean project history
- Separate your code into well-organized directories - Follow a consistent naming convention - Make use of pull requests
- Collaborate effectively by writing clear documentation - Maintain good communication within your team Keywords: GitHub, repository best practices, organization, structure, branch names, commit messages, project history, directories, naming conventions, pull requests, collaboration, documentation, effective communication
llm-tool provides a command-line utility for running large language models locally. It includes scripts for pulling models from the internet, starting them, and managing them using various commands such as 'run', 'ps', 'kill', 'rm', and 'pull'. Additionally, it offers a Python script named 'querylocal.py' for querying these models. The repository also come
- create a custom base image for a Cloud Workstation environment using a Dockerfile
. Uses:
Quantized models from
. Uses:
Quantized models from
