rugpt3small_based_on_gpt2

Introduction

The RUGPT3SMALL_BASED_ON_GPT2 model is a Russian language model developed by AI-FOREVER, based on the GPT-2 architecture. It is designed for text generation tasks and is compatible with both PyTorch and JAX libraries. The model targets the Russian language and benefits from the robust capabilities of the Transformers library.

Architecture

RUGPT3SMALL_BASED_ON_GPT2 utilizes a pretrained transformer architecture inspired by GPT-2. It was specifically designed for the Russian language, supporting a sequence length of up to 1024 tokens during pretraining. The model was further fine-tuned to handle a context size of 2048 tokens.

Training

The model was trained on 80 billion tokens over approximately three epochs. The training process was conducted by the SberDevices team, utilizing 32 GPUs and completing in roughly one week. The model was pretrained and fine-tuned to enhance its language understanding and generation capabilities for Russian text.

Guide: Running Locally

To run the RUGPT3SMALL_BASED_ON_GPT2 model locally:

1. Install Dependencies: Ensure you have Python and the necessary libraries installed, including PyTorch and Transformers.
2. Download the Model: Acquire the model files from Hugging Face's model hub.
3. Load the Model: Use the Transformers library to load the model and tokenizer.
4. Run Inference: Input text data and generate outputs using the model.

For optimal performance, it is recommended to use cloud-based GPUs such as those available from AWS, Google Cloud, or Azure.

License

The model and its accompanying resources are available under a license specified by its authors, typically found in the model repository or documentation. Ensure compliance with the license terms when utilizing the model for various applications.