PULI-LlumiX-Llama-3.1
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| Model Type | LLaMA-based Language Model |
| Architecture | LLaMA 3.1 |
| Context Length | 16,384 tokens |
| Precision | bfloat16 |
| HuggingFace | NYTK/PULI-LlumiX-Llama-3.1 |
What is PULI-LlumiX-Llama-3.1?
PULI-LlumiX-Llama-3.1 is a specialized language model built on the LLaMA 3.1 architecture, specifically enhanced for Hungarian language processing while maintaining English language capabilities. The model was developed by NYTK using the LLaMA-Factory framework and represents a significant advancement in multilingual AI modeling.
Implementation Details
The model underwent continued pretraining on an extensive dataset comprising 8.08 billion words of Hungarian text, including 763K long-form documents and Hungarian Wikipedia content. Additionally, it incorporates English language training data from Long Context QA (2 billion words) and BookSum (78 million words).
- Built on LLaMA 3.1 8B base architecture
- Supports sequence lengths up to 16,384 tokens
- Implements bfloat16 precision for efficient processing
- Trained using LLaMA-Factory framework
Core Capabilities
- Advanced Hungarian language understanding and generation
- Long-form content processing with extended context window
- Dual language proficiency in Hungarian and English
- Efficient integration with HuggingFace Transformers pipeline
- Suitable for both academic and practical applications
Frequently Asked Questions
Q: What makes this model unique?
The model's primary distinction lies in its specialized focus on Hungarian language processing while maintaining English capabilities, combined with an extensive context window of 16K tokens. The substantial training on Hungarian text (8.08B words) makes it particularly effective for Hungarian language tasks.
Q: What are the recommended use cases?
The model is well-suited for Hungarian text generation, long-form content processing, and bilingual applications requiring Hungarian-English language capabilities. It's particularly effective for tasks involving extensive context understanding and generation in Hungarian.
