InternLM2-Chat-7B
| Property | Value |
|---|---|
| Parameter Count | 7.74B |
| Model Type | Text Generation / Chat |
| Context Window | 200K tokens |
| License | Apache 2.0 (code), Custom (weights) |
| Paper | arXiv:2403.17297 |
What is internlm2-chat-7b?
InternLM2-Chat-7B is a state-of-the-art language model that represents the second generation of the InternLM family. It's specifically designed for practical applications, featuring an impressive 200K token context window and advanced capabilities across multiple domains including reasoning, mathematics, and code generation.
Implementation Details
The model utilizes a BF16 tensor type architecture and can be easily deployed using popular frameworks like Transformers, LMDeploy, or vLLM. It shows remarkable performance on various benchmarks, including MMLU (63.7%), GSM8K (70.7%), and HumanEval (59.8%).
- Supports both standard and streaming chat interfaces
- Compatible with multiple deployment options
- Optimized for production environments
Core Capabilities
- 200K context window with efficient long-text processing
- Advanced reasoning and mathematical problem-solving
- Strong code interpretation and generation
- Enhanced tool utilization and multi-step reasoning
- Comprehensive data analysis capabilities
Frequently Asked Questions
Q: What makes this model unique?
The model's standout feature is its 200K context window combined with state-of-the-art performance across various tasks, particularly in long-context scenarios. It provides near-perfect performance in "needle in a haystack" tasks with long inputs.
Q: What are the recommended use cases?
The model excels in scenarios requiring long context understanding, complex reasoning, code generation, and data analysis. It's particularly suitable for applications needing tool integration and multi-step problem solving.
