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.