metadata
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:
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>.