---
title: agent-data
canonical_url: "https://www.modelscope.cn/datasets/arcee-ai/agent-data"
md_url: "https://www.modelscope.cn/datasets/arcee-ai/agent-data.md"
repository: arcee-ai/agent-data
last_updated: 2026-07-23
license: mit
storage_size: "1.4 GB"
downloads: 80
stars: 0
---

# agent-data

> agent-data - arcee-ai 在 ModelScope 开源的数据集。Agent Data is designed for training AI agents, particularly in the domain of function calling and multi-turn conversations. It combines four distinct datasets - and is the exact mixture we used when training…

arcee-ai/agent-data 是 ModelScope 魔搭社区上的数据集，存储大小 1.4 GB，采用 mit 许可。

- **Repository**: arcee-ai/agent-data
- **License**: mit
- **Storage size**: 1.4 GB
- **Downloads**: 80
- **Stars**: 0
- **Last updated**: 2026-07-23

Source: https://www.modelscope.cn/datasets/arcee-ai/agent-data

---

<div align="center">
  <img src="https://i.postimg.cc/fzhqGMMf/9-Ji-CHw-Ub-QBqv-T-TYTY2-KAw.jpg" alt="Arcee-Agent" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0, 0, 0, 0.2), 0 6px 20px 0 rgba(0, 0, 0, 0.19); max-width: 100%; height: auto;">
</div>

Agent Data is designed for training AI agents, particularly in the domain of function calling and multi-turn conversations. It combines four distinct datasets - and is the exact mixture we used when training [Arcee-Agent](https://huggingface.co/arcee-ai/Arcee-Agent).

## Dataset Components

1. **Glaive Function Calling v2**
   - Notable feature: We have synthetically extended ~20k samples with sequential tool calls within the same response.

2. **Salesforce xlam Function Calling**

3. **Internlm's Agent-Flan series**

4. **Magpie Pro 300k**
   - Magpie is included to prevent overfitting, generalize the model to tasks beyond just function calling, and avoid catastrophic forgetting.

## Intended Use

This dataset is designed for:
- Training AI models in function calling and tool use
- Developing conversational AI agents
- Enhancing AI's ability to maintain context over extended interactions.