--- license: apache-2.0 base_model: - mistralai/Mistral-Small-24B-Base-2501 --- # Arcee Blitz Caller Beta This repository contains a beta version of the Arcee Blitz Caller, a powerful tool for automated function calling and tool selection. Below you'll find instructions on how to launch the service using vllm as well as detailed performance metrics. ## Overview Arcee Blitz Caller is built on top of the Mistral-Small-24B-Base-2501 model and is designed for efficient and accurate tool calling operations. ## Base Model - [mistralai/Mistral-Small-24B-Base-2501](https://huggingface.co./mistralai/Mistral-Small-24B-Base-2501) ## Quick Start To launch the service using vllm, run the following command: ```bash vllm serve arcee-ai/Arcee-Blitz-Caller \ --enable-auto-tool-choice \ --tool-call-parser hermes ``` ## Performance Metrics ### Non-Live Performance | Metric | Score | |--------|--------| | AST Accuracy | 85.15% | | Simple AST | 70.08% | | Multiple AST | 93.50% | | Parallel AST | 89.50% | | Parallel Multiple AST | 87.50% | ### Live Performance | Metric | Score | |--------|--------| | Accuracy | 74.19% | | Simple AST | 71.71% | | Multiple AST | 75.02% | | Parallel AST | 43.75% | | Parallel Multiple AST | 66.67% | ### Multi-Turn Performance | Metric | Score | |--------|--------| | Accuracy | 0.25% | | Base | 0.50% | | Miss Function | 0.00% | | Miss Parameter | 0.00% | | Long Context | 0.50% | | Relevance Detection | 61.11% | | Irrelevance Detection | 77.68% | > **Note:** The model demonstrates strong performance in single-turn interactions but currently shows limitations in multi-turn scenarios. We are actively developing new training data to enhance multi-turn capabilities. ## Current Status This is a beta release and is under active development. While the model shows promising results in many areas, users should be aware of its current limitations, particularly in multi-turn interactions. ## License This project is licensed under the Apache-2.0 License - see the [LICENSE](LICENSE) file for details.