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---
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. |