---
dataset_info:
  features:
  - name: messages
    list:
    - name: role
      dtype: string
    - name: content
      dtype: string
  splits:
  - name: train
    num_bytes: 46615078
    num_examples: 4431
  - name: validation
    num_bytes: 2461730
    num_examples: 234
  download_size: 49154345
  dataset_size: 49076808
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
---


## Usage

Conversations are ChatML `messages` lists. Tool calls are written inline in the
assistant content as MiniCPM5-style XML, so the chat template applies directly:

```python
from datasets import load_dataset
from transformers import AutoTokenizer

ds = load_dataset("koshuro/fable5-chatml", split="train")
tok = AutoTokenizer.from_pretrained("openbmb/MiniCPM5-1B")
text = tok.apply_chat_template(ds[0]["messages"], tokenize=False)
```

Assistant chain-of-thought is wrapped in `<think>…</think>`. Tool results are
`role: "tool"` messages, which the template renders as `<tool_response>`.