datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bfcl-testbfcl-ms
BFCL v3 — Malay (Bahasa Malaysia) Edition
A Malay edition of the Berkeley Function-Calling Leaderboard (BFCL) v3 — the standard benchmark for evaluating LLM function/tool calling.
5,011 test entries across 21 categories (simple, multiple, parallel, parallel_multiple, irrelevance, java, javascript, rest, sql, live_*, chatable, multi_turn_*), with ground-truth answer files unchanged so the official BFCL scoring harness runs unmodified.
What is translated to Malay:
User questions… See the full description on the dataset page: https://huggingface.co/datasets/khursani8/bfcl-ms.BFCL-V4-Parallel-Native
BFCL V4 Parallel Native
Native BFCL v4 single-turn parallel function-calling rows for decentralized multi-agent collaboration.
Source data comes from the official Berkeley Function Calling Leaderboard v4 data and possible-answer files.
Fields
id
official_category
task_type
user_prompt
function
ground_truth
Categories
live_parallel
live_parallel_multiple
parallel
parallel_multiple
Counts
train: 352 rows
eval: 88 rows
total: 440… See the full description on the dataset page: https://huggingface.co/datasets/OpenMLRL/BFCL-V4-Parallel-Native.BFCL-V4-Parallel-Multi-Turn
BFCL V4 Parallel Multi-Turn
Flattened current-turn rows from BFCL v4 multi-turn trajectories for decentralized multi-agent function-calling experiments.
Source data comes from the official Berkeley Function Calling Leaderboard v4 data and possible-answer files.
Fields
id
official_category
task_type
user_prompt
function
ground_truth
turn_index
Categories
multi_turn_base_step
multi_turn_long_context_step
multi_turn_miss_func_step… See the full description on the dataset page: https://huggingface.co/datasets/OpenMLRL/BFCL-V4-Parallel-Multi-Turn.BFCL-trajectories
AgentSuite/BFCL-trajectories
Per-model agent trajectory data for BFCL (public release).
Models: 26
Tasks per model: 4,441
One file per model: {model}.jsonl, one JSON object per line.
Fields: model_path, user_model_path, benchmark_name, task_name, sampling_params, user_sampling_params, messages, eval_result, meta.
sampling_params reflect each benchmark's own implementation; values the benchmark leaves unset are recorded as null (provider default).
Models… See the full description on the dataset page: https://huggingface.co/datasets/AgentSuite/BFCL-trajectories.bfcl_v4_web_searchbfcl-v1-non-live-ast-friendlibfcl-liquid-testbfcl-hammer-javajs-enhancedloom-benchmark-bfclbfcl-hammer-v2-dedup-hardidiombfcl-hammerbfcl-hammer-v2