update inference code

README.md

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 We're thrilled to introduce the Octopus Planner, the latest breakthrough in on-device language models from Nexa AI. Developed for the Planner-Action Agents Framework, Octopus Planner leverages state-of-the-art technology to enhance AI agents' decision-making processes directly on edge devices. By enabling rapid and efficient planning and action execution 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.
 
 ### Key Features of Octopus Planner:
-- **Efficient Planning**: Utilizes Phi-3 Mini architecture with only 3.8 billion parameters for high efficiency and low power consumption.
-- **Enhanced Accuracy**: Achieves a planning success rate of 97%, providing reliable and effective performance.
+- **Efficient Planning**: Utilizes fine-tuned plan model based on Phi-3 Mini (3.8 billion parameters) for high efficiency and low power consumption.
+- **Agent Framework**: Separates planning and action, allowing for specialized optimization and improved scalability.
+- **Enhanced Accuracy**: Achieves a planning success rate of 97% on benchmark dataset, providing reliable and effective performance.
 - **On-device Operation**: Designed for edge devices, ensuring fast response times and enhanced privacy by processing data locally.
-- **Cost-Effective**: Reduces operational costs by minimizing the key-value cache required, which also improves battery life.
-- **Fine-tuned**: Extensively fine-tuned on specialized tasks to ensure high accuracy and contextual understanding.
 
-## Innovative Framework
-The Octopus Planner introduces a specialized Planner and Action Agents Framework:
-- **Dual Model Architecture**: Separates planning and action, allowing for specialized optimization and improved scalability.
-- **Focused Training**: Employs fine-tuning over traditional long prompting, improving efficiency without sacrificing accuracy.
-- **Comprehensive Benchmarking**: Includes rigorous in-domain testing to validate the model's effectiveness in real-world scenarios.
 
 ## Example Usage
 Below is a code snippet to use Octopus Planner: