datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
HelpSteer2
HelpSteer2: Open-source dataset for training top-performing reward models
HelpSteer2 is an open-source Helpfulness Dataset (CC-BY-4.0) that supports aligning models to become more helpful, factually correct and coherent, while being adjustable in terms of the complexity and verbosity of its responses.
This dataset has been created in partnership with Scale AI.
When used to tune a Llama 3.1 70B Instruct Model, we achieve 94.1% on RewardBench, which makes it the best Reward Model as… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/HelpSteer2.HelpSteer
HelpSteer: Helpfulness SteerLM Dataset
HelpSteer is an open-source Helpfulness Dataset (CC-BY-4.0) that supports aligning models to become more helpful, factually correct and coherent, while being adjustable in terms of the complexity and verbosity of its responses.
Leveraging this dataset and SteerLM, we train a Llama 2 70B to reach 7.54 on MT Bench, the highest among models trained on open-source datasets based on MT Bench Leaderboard as of 15 Nov 2023.
This model is available on… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/HelpSteer.Helpsteer-preference-standardHelpSteer-AIF
HelpSteer: Helpfulness SteerLM Dataset
HelpSteer is an open-source Helpfulness Dataset (CC-BY-4.0) that supports aligning models to become more helpful, factually correct and coherent, while being adjustable in terms of the complexity and verbosity of its responses.
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
Disclaimer
This is only a subset created with distilabel to evaluate the first 1000 rows using AI Feedback (AIF) coming from GPT-4, only created for… See the full description on the dataset page: https://huggingface.co/datasets/alvarobartt/HelpSteer-AIF.HelpSteer2A reformatted version of nvidia/HelpSteer2 into both a multiturn config conversation and completion config config.
A v4 UUID doc_id is shared across the same document in each config, source, conversation, and completion.
helpsteer3-qwen35_annotated_humanHelpSteer-filtered
HelpSteer-filtered
This dataset is a highly filtered version of the nvidia/HelpSteer dataset.
❓ How this dataset was filtered:
I calculated the sum of the columns ["helpfulness," "correctness," "coherence," "complexity," "verbosity"] and created a new column named sum.
I changed some column names and added a empty column to match the Alpaca format.
The dataset was then filtered to include only those entries with a sum greater than or equal to 16.
🧐 More… See the full description on the dataset page: https://huggingface.co/datasets/Weyaxi/HelpSteer-filtered.HelpSteer-AIF-raw
HelpSteer: Helpfulness SteerLM Dataset
HelpSteer is an open-source Helpfulness Dataset (CC-BY-4.0) that supports aligning models to become more helpful, factually correct and coherent, while being adjustable in terms of the complexity and verbosity of its responses.
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
Disclaimer
This is only a subset created with distilabel to evaluate the first 1000 rows using AI Feedback (AIF) coming from GPT-4, only created for… See the full description on the dataset page: https://huggingface.co/datasets/alvarobartt/HelpSteer-AIF-raw.HelpSteer2_labeled_task
Dataset Card for HelpSteer2_labeled_task
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/CharlieJi/HelpSteer2_labeled_task/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/CharlieJi/HelpSteer2_labeled_task.HelpSteerA reformatted version of nvidia/HelpSteer into both a multiturn config conversation and completion config config.
A v4 UUID doc_id is shared across the same document in each config, source, conversation, and completion.
HelpSteer2_with_intent
Dataset Card for HelpSteer2_with_intent
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/CharlieJi/HelpSteer2_with_intent/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/CharlieJi/HelpSteer2_with_intent.HelpSteer2_prometheus
Dataset Card for HelpSteer2_prometheus
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/CharlieJi/HelpSteer2_prometheus/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/CharlieJi/HelpSteer2_prometheus.ChatML-HelpSteernvidia/HelpSteer in ChatML format, ready to use in HuggingFace TRL's SFT Trainer.
Python code used for conversion:
from datasets import load_dataset
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Felladrin/Llama-160M-Chat-v1")
dataset = load_dataset("nvidia/HelpSteer", split="train")
def format(columns):
prompt = columns["prompt"].strip()
response = columns["response"].strip()
messages = [
{
"role": "user"… See the full description on the dataset page: https://huggingface.co/datasets/Felladrin/ChatML-HelpSteer.helpsteer_combined
Dataset Card for "helpsteer_combined"
More Information needed
helpsteer2-binarized-granular-fullThis is the nvidia/Helpsteer2 training split binarized and sorted by length using the Llama3 tokenizer and categorized into multi- vs. single-turn subparts.
The 500 splits contain chosen responses between 500-1000 tokens, the 1000 split 1000+ tokens.A multi-turn example requires at least one pair of User and Assistant besides the main resposne to be categorized as such.If you don't care, there is a combined split, which includes everything just binarized, but note that ids are not the same… See the full description on the dataset page: https://huggingface.co/datasets/root-signals/helpsteer2-binarized-granular-full.Ko.HelpSteer원본 데이터셋: nvidia/HelpSteer
helpsteer3-qwen35_annotated_humanHelpSteer2_pairhelpsteer2_tail_modeldep_q10DPO-HelpSteer
Dataset Card for DPO-HelpSteer
Reformatted from nvidia/HelpSteer dataset.
The LION-series are trained using an empirically optimized pipeline that consists of three stages: SFT, DPO, and online preference learning (online DPO). We find simple techniques such as sequence packing, loss masking in SFT, increasing the preference dataset size in DPO, and online DPO training can significantly improve the performance of language models. Our best models (the LION-series) exceed the… See the full description on the dataset page: https://huggingface.co/datasets/Columbia-NLP/DPO-HelpSteer.HelpSteer-35k-jaNVIDIA が公開している SteerLM 向けのトライアルデータセット HelpSteerを日本語に自動翻訳したデータセットになります。SteerLM でのアライメントをお試ししたい際にご活用下さい。
SteerLM での LLM トレーニング方法については以下の URL を参考にして下さい。
Announcing NVIDIA SteerLM : https://developer.nvidia.com/blog/announcing-steerlm-a-simple-and-practical-technique-to-customize-llms-during-inference
NeMo Aligner : https://github.com/NVIDIA/NeMo-Aligner
SteerLM training user guide : https://docs.nvidia.com/nemo-framework/user-guide/latest/modelalignment/steerlm.html
[参考] SteerLM :… See the full description on the dataset page: https://huggingface.co/datasets/kunishou/HelpSteer-35k-ja.helpsteer2-binarized-granular-tinyThis is the nvidia/Helpsteer2 training split binarized and sorted by length using the Llama3 tokenizer and categorized into multi- vs. single-turn subparts.
The 500 splits contain chosen responses between 500-1000 tokens, the 1000 split 1000+ tokens.
A multi-turn example requires at least one pair of User and Assistant besides the main resposne to be categorized as such.
If you don't care, there is a combined split, which includes everything just binarized, but note that ids are not the same… See the full description on the dataset page: https://huggingface.co/datasets/root-signals/helpsteer2-binarized-granular-tiny.helpsteer2-helpfulness-preference
Citation
@misc{wang2024helpsteer2preferencecomplementingratingspreferences,
title={HelpSteer2-Preference: Complementing Ratings with Preferences},
author={Zhilin Wang and Alexander Bukharin and Olivier Delalleau and Daniel Egert and Gerald Shen and Jiaqi Zeng and Oleksii Kuchaiev and Yi Dong},
year={2024},
eprint={2410.01257},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2410.01257},
}
@misc{wang2024helpsteer2… See the full description on the dataset page: https://huggingface.co/datasets/Jennny/helpsteer2-helpfulness-preference.HelpSteer2-binarizedHelpsteer-armpreprocessed-helpsteer2-train-10knvidia-HelpSteer2-HindiThis dataset contains Hindi translation of the two columns "prompt" and "response" of the orginal dataset nvidia/HelpSteer2. The translation are stored in the columns "prompt-translation-hi" and "response-translation-hi" along with all the orginal columns.
HelpSteer3helpsteer3_goldSkywork-Reward-V2-Llama-3.1-8B-10khelpsteer3v2_annotated_Skywork-Skywork-Reward-V2-Llama-3-1-8B