Skip to content

InstaMatch as in Cloud Instance Matching for LLMs

Notifications You must be signed in to change notification settings

slashml/Instamatch

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Overview

InstaMatch is a cloud instance matching tool for machine learning models. It fetches model information from HuggingFace and recommends suitable cloud instances from AWS, Azure, and GCP based on the model's requirements.

Features

  • Fetch model information from HuggingFace API
  • Estimate model requirements (vCPUs and memory)
  • Recommend suitable cloud instances from AWS, Azure, and GCP
  • Display primary and backup recommendations

Installation

  1. Clone the repository: ```sh git clone https://github.com/yourusername/InstaMatch.git cd InstaMatch ```

  2. Create and activate a virtual environment: ```sh python3 -m venv venv source venv/bin/activate ```

  3. Install the required dependencies: ```sh pip install -r requirements.txt ```

  4. Set up your HuggingFace API token in a `.env` file: ```sh echo "HUGGING_FACE_TOKEN=your_huggingface_token" > .env ```

Usage

  1. Run the application: ```sh python app.py ```

  2. Open the provided URL in your browser.

  3. Enter a model name from HuggingFace (e.g., `gpt2`, `bert-base-uncased`) and click "Get Recommendations".

  4. View the model requirements and cloud instance recommendations.

Files

  • `app.py`: Main application file
  • `cloud_instances.csv`: CSV file containing cloud instance data
  • `requirements.txt`: List of required Python packages
  • `utils/`: Utility functions and modules

License

This project is licensed under the MIT License." > README.md

git add README.md git commit -m "Add README file"

About

InstaMatch as in Cloud Instance Matching for LLMs

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages