Octopus-v2
| Property | Value |
|---|---|
| Parameter Count | 2.51B |
| Model Type | Text Generation |
| Base Model | Google Gemma-2B |
| License | CC-BY-NC-4.0 |
| Paper | ArXiv |
| Tensor Type | FP16 |
What is Octopus-v2?
Octopus-v2 is an advanced open-source language model specifically designed for on-device function calling and Android API integration. Built on Google's Gemma-2B architecture, it introduces a revolutionary functional token strategy that enables GPT-4-level accuracy while significantly improving inference speed.
Implementation Details
The model utilizes a unique functional token approach for both training and inference stages, making it particularly efficient for edge computing devices. It's optimized for FP16 precision and can be easily deployed on Android devices.
- Achieves 99.5% accuracy in function calling tasks
- 168% faster than GPT-4-turbo on inference
- 36x faster than Llama7B + RAG solutions
- Optimized for Android API integration
Core Capabilities
- Efficient on-device processing for Android systems
- Generation of individual, nested, and parallel function calls
- High-speed inference with minimal latency (0.38s average)
- Specialized for Android API orchestration
- Support for complex system management tasks
Frequently Asked Questions
Q: What makes this model unique?
Octopus-v2's distinctive feature is its functional token strategy, which enables it to achieve GPT-4-level accuracy while operating on-device with significantly faster inference speeds than traditional RAG-based approaches.
Q: What are the recommended use cases?
The model is specifically optimized for Android system management, device orchestration, and API integration. It's ideal for applications requiring efficient on-device function calling and system control capabilities.
