| Property | Value |
|---|---|
| Parameter Count | 8 Billion |
| License | Apache-2.0 |
| Author | Shanghai AI Laboratory |
| Paper | arXiv:2403.17297 |
What is internlm3-8b-instruct?
InternLM3-8B-Instruct is a state-of-the-art instruction-following language model developed by Shanghai AI Laboratory. What sets it apart is its remarkable efficiency - achieving superior performance while being trained on just 4 trillion high-quality tokens, representing a 75% reduction in training costs compared to similar models.
Implementation Details
The model implements a dual-mode architecture that supports both deep thinking for complex reasoning tasks and regular conversation modes. It's optimized for deployment with various frameworks including Transformers, LMDeploy, Ollama, and vLLM, with options for 4-bit and 8-bit quantization to reduce memory requirements.
- Advanced reasoning capabilities surpassing Llama3.1-8B and Qwen2.5-7B
- Efficient training methodology using only 4T tokens
- Supports both deep thinking and conversational modes
- Multiple deployment options with various optimization levels
Core Capabilities
- Strong performance in mathematical reasoning (83.0% on MATH-500)
- Excellence in knowledge-intensive tasks (CMMU score: 83.1)
- Advanced coding capabilities (82.3% on HumanEval)
- Robust long-context understanding (87.9% on RULER)
- High-quality chat interactions (8.59 on MT-Bench-101)
Frequently Asked Questions
Q: What makes this model unique?
The model's standout feature is its ability to achieve state-of-the-art performance while using significantly fewer training tokens than competitors, demonstrating remarkable efficiency in both training and deployment.
Q: What are the recommended use cases?
The model excels in mathematical reasoning, knowledge-intensive tasks, coding, and general conversation. It's particularly well-suited for applications requiring deep analytical thinking while maintaining natural conversation abilities.