Vikhr Gemma 2 B instruct G G U F

Introduction

The Vikhr-Gemma-2B-Instruct model is a powerful instructive text-generation model based on the Gemma 2 architecture with 2 billion parameters. It is specifically trained on a Russian-language dataset, GrandMaster-PRO-MAX, and is part of the Vikhrmodels collection on Hugging Face.

Architecture

The model utilizes the llamacpp library and is designed for Russian language text generation. It is built on the base model Vikhrmodels/Vikhr-Gemma-2B-instruct and supports various configurations for model perplexity analysis, indicating its adaptability and performance optimization.

Training

The model was trained on the GrandMaster-PRO-MAX dataset, which is specifically tailored for Russian language instruction tasks. Model perplexity scores are provided for various configurations, showing performance metrics on datasets like VELES and WIKITEXT-2, with lower perplexity values indicating better performance.

Guide: Running Locally

To run the Vikhr-Gemma-2B-Instruct model locally:

1. Clone the Repository: Download the model files from the Hugging Face repository.
2. Install Dependencies: Ensure all necessary libraries, such as llamacpp, are installed in your environment.
3. Load the Model: Use the model loading functions from the llamacpp library.
4. Run Inference: Use the model for text generation tasks as per your requirements.

For optimal performance, consider using cloud GPUs, such as those offered by AWS, Google Cloud, or Azure.

License

The Vikhr-Gemma-2B-Instruct model is released under the Apache 2.0 license, which allows for both personal and commercial use with appropriate attribution.