Giga-Embeddings-Instruct

Introduction

Giga-Embeddings-Instruct is a model developed by AI-SAGE, designed for embedding extraction in multiple languages, including Russian and English. It supports various features like safetensors, gigarembed, and mteb, making it versatile for a range of applications.

Architecture

The model employs advanced embedding techniques to facilitate feature extraction across different languages. It is optimized for performance and accuracy, leveraging custom code to enhance its capabilities.

Training

Details about the specific training methodologies and datasets used are not explicitly provided. However, it is implied that the model has been trained using diverse data to support its multilingual and multifunctional features.

Guide: Running Locally

To run Giga-Embeddings-Instruct locally, follow these steps:

1. Clone the Repository: Start by cloning the repository from Hugging Face.
2. Install Dependencies: Ensure all required libraries and dependencies are installed, including the Hugging Face Transformers library.
3. Download the Model: Use the Hugging Face model hub to download the Giga-Embeddings-Instruct model files.
4. Run the Model: Use a Python script or Jupyter Notebook to load and run the model for embedding extraction tasks.

Suggested Cloud GPUs

For enhanced performance, consider using cloud GPU services like AWS EC2, Google Cloud Platform, or Azure. These platforms provide scalable resources suitable for running complex models efficiently.

License

The Giga-Embeddings-Instruct model is released under the MIT License, allowing for flexibility in use and distribution.