đ Mongolian GPT2
This project aims to develop a powerful language generation model for Mongolian. Leveraging the initial code and data provided by @patrickvonplaten and other Hugging Face members, it's expected to gain an initial understanding with relative ease.
đ Quick Start
The primary goal of this project is to create a proficient language generation model tailored for the Mongolian language. Thanks to the foundational work done by @patrickvonplaten and other Hugging Face team members, getting started shouldn't be overly challenging.
⨠Features
- Model: A randomly initialized GPT2 model is employed.
- Datasets: The OSCAR dataset, accessible via the
datasets library, can be utilized. There's also a possibility of private crawling and integrating additional data if time permits.
- Expected Outcome: The project aims to achieve an understandable Mongolian text generation model.
đĻ Installation
No specific installation steps are provided in the original document.
đģ Usage Examples
No code examples are provided in the original document.
đ Documentation
Model
The model used is a randomly initialized GPT2 model.
Datasets
- OSCAR: We can use the OSCAR dataset, which is accessible through the
datasets library.
- Script: A causal language modeling script for Flax is available here. It can be used with little to no code modifications.
- Future Plan: If time allows, private crawling will be attempted and the crawled data will be integrated into the existing datasets.
Expected Outcome
The expected outcome is a model capable of generating understandable Mongolian text.
Challenges
The main challenge lies in the lack of data. The Mongolian subset of the OSCAR dataset is only 2.2G. Further research on data acquisition methods might be necessary.
đ§ Technical Details
No in - depth technical details are provided in the original document.
đ License
No license information is provided in the original document.
â ī¸ Important Note
The lack of data is a significant challenge as the Mongolian part of the OSCAR dataset is only 2.2G. Research on ways to acquire more data may be required.
đĄ Usage Tip
The causal language modeling script for Flax can be used with minimal code changes, which is a great advantage for quick implementation.
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Transformers