datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.APIGen-MT-5k
Summary
APIGen-MT is an automated agentic data generation pipeline designed to synthesize verifiable, high-quality, realistic datasets for agentic applications
This dataset was released as part of APIGen-MT: Agentic PIpeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
Code: https://github.com/apigen-mt/apigen-mt.github.io
The repo contains 5000 multi-turn trajectories collected by APIGen-MT
This dataset is a subset of the data used to train the xLAM-2 model… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/APIGen-MT-5k.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.apigen-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.synth-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.API_Gen_ShareGPTAPIGen-50k50,000 samples from argilla/apigen-function-calling
APIGen-MT-5k
Summary
APIGen-MT is an automated agentic data generation pipeline designed to synthesize verifiable, high-quality, realistic datasets for agentic applications
This dataset was released as part of APIGen-MT: Agentic PIpeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
Code: https://github.com/apigen-mt/apigen-mt.github.io
The repo contains 5000 multi-turn trajectories collected by APIGen-MT
This dataset is a subset of the data used to train the xLAM-2… See the full description on the dataset page: https://huggingface.co/datasets/WalterWangtao/APIGen-MT-5k.agenttune-apigen-SFT-qwen3-0.6b-tracesAPIGen-MT-46kDans-Toolmaxx-Functions-apigenAPIGen_5k_cleaned_tau2tool_nothink_replacedv3APIGen-MT-5k-with-thinkAPIGen-MT-5k-sharegpt
Dataset Card for APIGen-MT-5k-sharegpt
This dataset is the sharegpt format of the original Salesforce/APIGen-MT-5k dataset. It is primarily designed for fine-tuning large language models (LLMs) for function calling and multi-turn conversations.
Dataset Description
The original Salesforce/APIGen-MT-5k dataset contains conversations between users and a language model, focusing on API usage and tool invocation scenarios. We have converted this dataset into the ShareGPT… See the full description on the dataset page: https://huggingface.co/datasets/Beryex/APIGen-MT-5k-sharegpt.apigen-mt-5k-friendli
Used in axolotl
datasets:
- path: minpeter/apigen-mt-5k-friendli
data_files:
- train.jsonl
- test.jsonl
type: chat_template
roles_to_train: ["assistant"]
field_messages: messages
message_property_mappings:
role: role
content: contentchat_template: tokenizer_default
APIGen-MT-5k-tool-formatapi-generatorsynth-apigen-llama-test
Dataset Card for synth-apigen-llama-test
This dataset has been created with distilabel.
The pipeline script was uploaded to easily reproduce the dataset:
synth_apigen.py.
It can be run directly using the CLI:
distilabel pipeline run --script "https://huggingface.co/datasets/plaguss/synth-apigen-llama-test/raw/main/synth_apigen.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-test.apigen-function-calling
apigen-function-calling
Converted version of argilla/apigen-function-calling in uniform OpenAI-compatible tool-calling format.
Source
Original dataset: argilla/apigen-function-calling — ~109k single-turn function-calling examples generated via the APIGen pipeline, covering diverse real-world APIs (superset of xLAM-60k with additional sources).
Schema
Column
Type
Description
messages
JSON string
[user_msg, assistant_msg_with_tool_calls]… See the full description on the dataset page: https://huggingface.co/datasets/tuandunghcmut/apigen-function-calling.apigen-with-thinking-1.5kI added thinking traces to 1.5k samples from Salesforce/APIGen-MT-5k using gpt-oss-120b with high reasoning effort.
To prevent HF from modifying the fields, I stored each sample as a json string.
from datasets import load_dataset
ds = load_dataset("nbroad/apigen-with-thinking-1.5k")['train']
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")
import json
def tokenize(sample):
full_ids = tokenizer.apply_chat_template(… See the full description on the dataset page: https://huggingface.co/datasets/nbroad/apigen-with-thinking-1.5k.negative_FC_from_apigenaprm-amityco_apigen_tau_bench_split_turn