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README.md
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license: cc-by-nc-4.0
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#
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We're thrilled to introduce the
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### Key Features of
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- **Efficient Planning**: Utilizes fine-tuned plan model based on Phi-3 Mini (
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- **Agent Framework**: Separates planning and action, allowing for specialized optimization and improved scalability.
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- **Enhanced Accuracy**: Achieves a planning success rate of
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- **On-device Operation**: Designed for edge devices, ensuring fast response times and enhanced privacy by processing data locally.
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## Example Usage
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Below is a
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<p align="center" width="100%">
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<a><img src="1-demo.png" alt="ondevice" style="width: 80%; min-width: 300px; display: block; margin: auto;"></a>
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</p>
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license: cc-by-nc-4.0
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# Octo-planner: On-device Language Model for Planner-Action Agents Framework
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We're thrilled to introduce the Octo-planner, the latest breakthrough in on-device language models from Nexa AI. Developed for the Planner-Action Agents Framework, Octo-planner enables rapid and efficient planning without the need for cloud connectivity, this model together with [Octopus-V2](https://huggingface.co/NexaAIDev/Octopus-v2) can work on edge devices locally to support AI Agent usages.
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### Key Features of Octo-planner:
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- **Efficient Planning**: Utilizes fine-tuned plan model based on Phi-3 Mini (2.51 billion parameters) for high efficiency and low power consumption.
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- **Agent Framework**: Separates planning and action, allowing for specialized optimization and improved scalability.
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- **Enhanced Accuracy**: Achieves a planning success rate of 98.1% on benchmark dataset, providing reliable and effective performance.
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- **On-device Operation**: Designed for edge devices, ensuring fast response times and enhanced privacy by processing data locally.
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## Example Usage
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Below is a demo of Octo-planner:
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<p align="center" width="100%">
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<a><img src="1-demo.png" alt="ondevice" style="width: 80%; min-width: 300px; display: block; margin: auto;"></a>
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</p>
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