cuneiform

Introduction
The Cuneiform Language Translator is a neural network model designed to translate Sumerian and Akkadian languages written in cuneiform into English. This model is built to handle text transcribed in the CDLI ATF format, focusing on translating ancient languages using modern text prompts.

Architecture
The model is implemented using the Transformers library in PyTorch and leverages the T5 model architecture. It is focused on text-to-text generation tasks, specifically for cuneiform script translation.

Training
The model was trained on cuneiform scripts transcribed in the CDLI ATF format. It is capable of translating from Akkadian and Sumerian to English and vice versa. However, it was not explicitly trained for direct translation between the ancient languages, though it can attempt such translations.

Guide: Running Locally

1. Ensure you have Python and PyTorch installed on your machine.
2. Clone the repository and navigate to the directory.
3. Install the necessary dependencies using pip.
4. Load the model using the Transformers library and provide input in the specified format for translation tasks.

For optimal performance, especially when dealing with large datasets or requiring faster inference, it is recommended to use cloud GPUs available on platforms such as AWS or Google Cloud.

License
The Cuneiform Language Translator is licensed under the MIT License, allowing for flexible use, modification, and distribution of the software.