Vikhr-7B-instruct_0.4
| Property | Value |
|---|---|
| Parameter Count | 7.63B |
| Model Type | Instruction-tuned LLM |
| Languages | Russian, English |
| Research Paper | arXiv:2405.13929 |
| Tensor Type | BF16 |
What is Vikhr-7B-instruct_0.4?
Vikhr-7B-instruct_0.4 is a sophisticated bilingual language model designed for both Russian and English language processing. This version represents a significant upgrade with enhanced SFT (Supervised Fine-Tuning) data integration and improved stability for JSON handling and multi-turn conversations.
Implementation Details
The model is built on the LLaMA architecture and implements Flash Attention 2 for optimal performance. It supports text generation tasks and can be easily integrated using the Transformers library. The model utilizes bfloat16 precision for efficient computation while maintaining accuracy.
- Implements Flash Attention 2 for improved performance
- Supports both Russian and English language processing
- Enhanced stability for long-context operations
- Optimized for JSON handling and multi-turn conversations
Core Capabilities
- Bilingual text generation and processing
- Efficient handling of long-context conversations
- Stable JSON processing
- Support for multi-turn dialogue systems
- Integration with text-generation-inference endpoints
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its specialized optimization for Russian and English language processing, enhanced SFT training, and improved stability in handling complex tasks like JSON processing and multi-turn conversations.
Q: What are the recommended use cases?
The model is particularly well-suited for bilingual applications requiring Russian-English language processing, conversational AI systems, and applications requiring stable JSON handling and long-context understanding.
