Vikhr-Qwen-2.5-1.5B-Instruct-GGUF
| Property | Value |
|---|---|
| Parameter Count | 1.54B |
| License | Apache 2.0 |
| Format | GGUF (llama.cpp compatible) |
| Languages | Russian, English |
| Base Model | Qwen-2.5-1.5B-Instruct |
What is Vikhr-Qwen-2.5-1.5B-Instruct-GGUF?
Vikhr-Qwen-2.5-1.5B-Instruct-GGUF is a specialized bilingual language model optimized for Russian and English text processing. Built upon the Qwen-2.5-1.5B-Instruct architecture, this model has been specifically fine-tuned on the GrandMaster-PRO-MAX dataset to enhance its performance in handling Russian language tasks while maintaining strong English language capabilities.
Implementation Details
The model implements the efficient GGUF format, making it compatible with llama.cpp for optimized inference. With 1.54 billion parameters, it strikes a balance between computational efficiency and performance.
- Optimized for llama.cpp deployment
- GGUF format for efficient inference
- Trained on specialized Russian dataset GrandMaster-PRO-MAX
- Instruction-tuned architecture
Core Capabilities
- Bilingual processing in Russian and English
- High-efficiency text processing
- Precise response generation
- Fast task execution
- Instruction-following capabilities
Frequently Asked Questions
Q: What makes this model unique?
This model's unique strength lies in its specialized optimization for Russian language processing while maintaining English capabilities, implemented in the efficient GGUF format for practical deployment.
Q: What are the recommended use cases?
The model is particularly well-suited for bilingual applications requiring Russian and English text processing, including content generation, translation assistance, and instruction-following tasks.
