Agent Training Examples In CoPaw Format

LocoreMind provides an example dataset for training agent models with tool calling capabilities. It is formatted for compatibility with the CoPaw-Flash-9B model and uses a standard three-role message structure. The dataset was last updated in April 2026.

Use Cases

• Fine-tuning language models to generate 'tool_call' XML tags within 'assistant' content.
• Training models to process 'tool_response' data enclosed in <tool_response> tags within 'user' content.
• Benchmarking agent performance on structured tasks using the defined 'system', 'user', 'assistant' message roles.
• Developing tool-calling agents using the snake_case tool name convention specified in the format.

Strengths

• Formatted specifically for CoPaw-Flash-9B compatibility.
• Defines a clear structure with three roles: system, user, and assistant.

Limitations

• The dataset is explicitly labeled as an 'example', suggesting limited size and scope for production training.
• No information is provided on the number of examples, topics covered, or diversity of tool calls.
• The synthetic or example nature of the data may not reflect real-world complexity or distribution.

Provenance

Source

LocoreMind via Hugging Face.

Collection Method

Synthetic or curated example dataset, method unknown.

Freshness

Last updated in April 2026.