Llama-3.1-8B-Instuct-Uz
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| Model Type | Instruction-tuned Language Model |
| License | Llama 3.1 |
| Tensor Type | BF16 |
| Languages | Uzbek, English |
What is Llama-3.1-8B-Instuct-Uz?
Llama-3.1-8B-Instuct-Uz is an advanced bilingual language model specifically optimized for Uzbek and English language processing. Developed by a team including Eldor Fozilov, Azimjon Urinov, and Khurshid Juraev, this model represents a significant step forward in bringing state-of-the-art language AI capabilities to the Uzbek language community.
Implementation Details
The model is built upon the Meta-Llama-3.1-8B-Instruct architecture and has been carefully instruction-tuned using a combination of public and synthetic data. It utilizes the transformers library and supports various deployment options, including local inference and quantized implementations.
- Achieves 27.42 BLEU score for Uzbek-to-English translation
- Demonstrates 82.42% accuracy in Uzbek sentiment analysis
- Maintains 62.78% accuracy on MMLU (English) benchmarks
- Supports both CPU and GPU inference with bfloat16 precision
Core Capabilities
- Bilingual text generation and translation
- Sentiment analysis in Uzbek
- News classification
- Question-answering in both languages
- Summarization tasks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized optimization for the Uzbek language while maintaining strong English language capabilities. It shows significant improvements over the base model in Uzbek-specific tasks while preserving general language understanding abilities.
Q: What are the recommended use cases?
The model is ideal for Uzbek-English translation tasks, sentiment analysis of Uzbek text, news classification, and general language understanding tasks in both languages. It's particularly suited for applications requiring bilingual capabilities in these language pairs.
