datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NexusRaven_API_evaluation
NexusRaven API Evaluation dataset
Please see blog post or NexusRaven Github repo for more information.
License
The evaluation data in this repository consists primarily of our own curated evaluation data that only uses open source commercializable models. However, we include general domain data from the ToolLLM and ToolAlpaca papers. Since the data in the ToolLLM and ToolAlpaca works use OpenAI's GPT models for the generated content, the data is not commercially… See the full description on the dataset page: https://huggingface.co/datasets/Nexusflow/NexusRaven_API_evaluation.apigen-function-calling
Dataset card for argilla/apigen-function-calling
This dataset is a merge of argilla/Synth-APIGen-v0.1
and Salesforce/xlam-function-calling-60k, making
over 100K function calling examples following the APIGen recipe.
Prepare for training
This version is not ready to do fine tuning, but you can run a script like prepare_for_sft.py
to prepare it, and run the same recipe that can be found in
argilla/Llama-3.2-1B-Instruct-APIGen-FC-v0.1#training-procedure.
Modify the prompt… See the full description on the dataset page: https://huggingface.co/datasets/argilla/apigen-function-calling.Synth-APIGen-v0.1
Dataset card for Synth-APIGen-v0.1
This dataset has been created with distilabel.
Pipeline script: pipeline_apigen_train.py.
Dataset creation
It has been created with distilabel==1.4.0 version.
This dataset is an implementation of APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets in distilabel,
generated from synthetic functions. The process can be summarized as follows:
Generate (or in this case modify) python… See the full description on the dataset page: https://huggingface.co/datasets/argilla/Synth-APIGen-v0.1.APIGen-MT-5k-with-cot-v1-deepseek_deepseeksynth-apigen-qwen-exec
Dataset Card for synth-apigen-qwen-exec
This dataset has been created with distilabel.
The pipeline script was uploaded to easily reproduce the dataset:
apigen_exec.py.
It can be run directly using the CLI:
distilabel pipeline run --script "https://huggingface.co/datasets/plaguss/synth-apigen-qwen-exec/raw/main/apigen_exec.py"
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in… See the full description on the dataset page: https://huggingface.co/datasets/plaguss/synth-apigen-qwen-exec.apigen-smollm-trl-FC
Dataset card for argilla-warehouse/apigen-smollm-trl-FC
This dataset is a merge of argilla/Synth-APIGen-v0.1
and Salesforce/xlam-function-calling-60k, and was prepared for training using the script
prepare_for_sft.py that can be found in the repository files.
References
@article{liu2024apigen,
title={APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets},
author={Liu, Zuxin and Hoang, Thai and Zhang, Jianguo and Zhu, Ming and… See the full description on the dataset page: https://huggingface.co/datasets/argilla-warehouse/apigen-smollm-trl-FC.synth-apigen-qwen
Dataset Card for argilla-warehouse/synth-apigen-qwen
This dataset has been created with distilabel.
The pipeline script was uploaded to easily reproduce the dataset:
synth_apigen.py.
Dataset creation
This dataset is a replica in distilabel of the framework
defined in: APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.
Using the seed dataset of synthetic python functions in argilla-warehouse/python-seed-tools,
the… See the full description on the dataset page: https://huggingface.co/datasets/argilla-warehouse/synth-apigen-qwen.synth-apigen-llama-exec
Dataset Card for synth-apigen-llama-exec
This dataset has been created with distilabel.
The pipeline script was uploaded to easily reproduce the dataset:
apigen_exec.py.
It can be run directly using the CLI:
distilabel pipeline run --script "https://huggingface.co/datasets/plaguss/synth-apigen-llama-exec/raw/main/apigen_exec.py"
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in… See the full description on the dataset page: https://huggingface.co/datasets/plaguss/synth-apigen-llama-exec.starcoder-apis-2starcoderdata-apisstarcoder-apis-1starcoder-apis-0apigen-tau-bench-split-turnhermes_salesforce_apigen_tool_useapigen-synth-trl
Dataset card
This dataset is a version of argilla/Synth-APIGen-v0.1 prepared for
fine-tuning using trl. To generate it, the following script was run:
from datasets import load_dataset
from jinja2 import Template
SYSTEM_PROMPT = """
You are an expert in composing functions. You are given a question and a set of possible functions.
Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
If none of the functions can be used, point it out… See the full description on the dataset page: https://huggingface.co/datasets/argilla-warehouse/apigen-synth-trl.apigen-mt-5k-parsed
[PARSED] APIGen-MT-5k
The data in this dataset is a full of the original Salesforce/APIGen-MT-5k
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
apigen-mt-5k
yes
no
yes
complex
5k
This is a re-parsing formatting dataset for the APIGen-MT-5k official dataset.
Load the dataset
from datasets import load_dataset
ds = load_dataset("minpeter/apigen-mt-5k-parsed")
print(ds)
# DatasetDict({
# train: Dataset({
#… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/apigen-mt-5k-parsed.java_code_api_generationsynth-apigen-llama
Dataset Card for argilla-warehouse/synth-apigen-llama
This dataset has been created with distilabel.
The pipeline script was uploaded to easily reproduce the dataset:
synth_apigen.py.
Dataset creation
This dataset is a replica in distilabel of the framework
defined in: APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.
Using the seed dataset of synthetic python functions in argilla-warehouse/python-seed-tools,
the… See the full description on the dataset page: https://huggingface.co/datasets/argilla-warehouse/synth-apigen-llama.APIBenchThis dataset is derived from APIBench dataset by running the following script:
# clone gorilla repo
# process apibench data and upload as a dataset to hf hub
import json
import os
import dotenv
import pandas as pd
from datasets import Dataset
from huggingface_hub import login
dotenv.load_dotenv()
os.system("git clone https://github.com/ShishirPatil/gorilla.git")
# login to huggingface
login(os.environ["HF_API_KEY"])
def read_jsonl_as_df(file_path):
data = []
with open(file_path… See the full description on the dataset page: https://huggingface.co/datasets/rbiswasfc/APIBench.text-guided-vc-google-tts-api
Dataset Card for "text-guided-vc-google-tts-api"
More Information needed
agentic-tool-use-multi-api-orchestration-2026
⚡ Agentic Tool-Use, Multi-API Calling & Autonomous Function Orchestration (2026)
Official 100-sample production preview of the Agentic Tool-Use & Multi-API Orchestration Suite (2026) by BeatsProm AI Research Lab. Engineered for parallel tool calling (<tool_call>), strict JSON-schema enforcement, stateful cursor pagination, and self-healing API error recovery.
🏛️ THE 20 AGENTIC OPERATIONAL CORES:
Parallel Portfolio Rebalancing: Multi-leg execution with… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/agentic-tool-use-multi-api-orchestration-2026.text-guided-vc-google-tts-api-v0
Dataset Card for "text-guided-vc-google-tts-api"
More Information needed
starcoder-filtered-apisgorilla-apibenchevalap-comparing-albert-api-models-v11-12-2025-107
Comparing Albert-API models v11-12-2025 (ID: 107)
Comparing albert models on MFS-AIA datasets
Overview
This dataset contains 20 experiments
from the EvalAP evaluation platform.
Datasets: Assistant IA - QA, MFS_questions_v01
Models evaluated: albert-large, albert-small, openweight-large, openweight-medium, openweight-small
Metrics: generation_time, judge_notator, judge_precision, nb_tokens_completion, nb_tokens_prompt, output_length
Scores
Assistant IA… See the full description on the dataset page: https://huggingface.co/datasets/AgentPublic/evalap-comparing-albert-api-models-v11-12-2025-107.text-guided-vc-google-tts-api-speech_tokenizer
Dataset Card for "text-guided-vc-google-tts-api-speech_tokenizer"
More Information needed
v3-eval-rubric-v2-apiapi-sequencing-training-pool
API sequencing training pool
Requests paired with the sequence of API calls that answers them, from three public datasets read
at the pinned revisions named below and from a fourth that the builder of this pool generated,
laid out twice. Train on either layer or on both.
pool.jsonl
Every source rewritten into one shape, 136292 rows, one JSON object per line, with these fields.
Field
What it holds
id
a row identifier unique within this file
request… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/api-sequencing-training-pool.API-Bank-RLVR
API-Bank-RLVR
Reinforcement Learning with Verifiable Rewards dataset derived from API-Bank stepwise tool-call tasks.
Splits:
train
validation
Columns (typical):
prompt: User-facing prompt text (string)
reward_model: JSON string or object containing ground truth (e.g., {"style": "rule", "ground_truth": {"name": str, "parameters": dict}})
Notes:
Prompts are prepared for tool-call generation.
Ground truth matches API-Bank evaluate semantics (name + parameters).
agenttune-apigen-SFT-qwen3-0.6b-traces