SOLAR-10.7B-Instruct-v1.0
| Property | Value |
|---|---|
| Parameter Count | 10.7B |
| License | CC-BY-NC-4.0 |
| Paper | Research Paper |
| Training Data | Alpaca-GPT4, OpenOrca, Orca DPO pairs, UltraFeedback |
What is SOLAR-10.7B-Instruct-v1.0?
SOLAR-10.7B-Instruct-v1.0 is an advanced language model that implements a novel depth up-scaling (DUS) methodology, achieving remarkable performance that surpasses models up to 30B parameters. This instruction-tuned version is specifically optimized for single-turn conversations, demonstrating superior capabilities in various NLP tasks.
Implementation Details
The model utilizes state-of-the-art instruction fine-tuning methods including supervised fine-tuning (SFT) and direct preference optimization (DPO). It's built upon the Mistral 7B architecture with upscaled layers and continued pre-training.
- Implements innovative depth up-scaling (DUS) methodology
- Combines multiple high-quality training datasets
- Achieves 74.20 on the H6 benchmark
- Optimized for FP16 precision
Core Capabilities
- Superior single-turn conversation handling
- Strong performance in general NLP tasks
- Efficient parameter utilization (10.7B)
- Contamination-free benchmark performance
Frequently Asked Questions
Q: What makes this model unique?
The model's unique depth up-scaling approach and careful instruction fine-tuning enable it to outperform much larger models, including Mixtral 8X7B, while maintaining a relatively compact size of 10.7B parameters.
Q: What are the recommended use cases?
The model is optimized for single-turn conversations and general NLP tasks. It's particularly well-suited for applications requiring precise responses in a single interaction, though it's less optimal for multi-turn chat scenarios.
