datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
helpsteer2_dpo_nonverboseHelperSteer 2, formatted in DPO format (prompt, chosen, rejected).
in main branch there is a custom scoring correct > helpful > -verbosity
in each branch we have preference pairs for only correct, helpful, verbosity, coherence, complexity
Please note that only correct and helpful has strong inter-rater agreement in the HelpSteer2 paper
This is the notebook used to produce the dataset… See the full description on the dataset page: https://huggingface.co/datasets/wassname/helpsteer2_dpo_nonverbose.ouroboros-trace-help
Trace Help — does an execution trace help a model answer questions about a run?
In one minute. Twelve small programs in six languages (Python, JavaScript, C,
C++, Go, Elixir). Each was run once with a fixed command. Five questions per
program ask what actually happened on that one run: how many times a function
was called, what a particular call returned, what it was called with, whether a
function ran at all, which function raised. Sixty questions in total.
Every record carries… See the full description on the dataset page: https://huggingface.co/datasets/digitable-lol/ouroboros-trace-help.helpsteer2-categorized-prompts
HelpSteer2 Categorized Prompts
Dataset Summary
A curated collection of 540 instruction prompts derived from nvidia/HelpSteer2 and several complementary open datasets, enriched with category labels for use in instruction-tuning, benchmark evaluation, and prompt engineering research.
Prompts are clean plain text, ready for direct use in fine-tuning pipelines, benchmarks, and prompt engineering workflows.
Categories
Category
Count
Description
BASIC… See the full description on the dataset page: https://huggingface.co/datasets/atekrugis/helpsteer2-categorized-prompts.neovim-helpChatML-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.MamaBench
Dataset Card for MamaBench
Dataset Summary
MamaBench is a counterfactual clinical benchmark for evaluating the robustness of large language models on maternal and child health diagnostic reasoning. It consists of 217 counterfactual case pairs, each pairing an original clinical vignette with a systematically perturbed counterfactual variant, designed to test whether a model's diagnostic reasoning is sensitive to clinically meaningful changes rather than relying on… See the full description on the dataset page: https://huggingface.co/datasets/HelpMum-Personal/MamaBench.HelpSteer-hindihelpsteer3-tr
HelpSteer3-TR
NVIDIA HelpSteer3 veri setinin Türkçe çevirisidir. Bu veri seti, büyük dil modellerini (LLM) kullanıcı taleplerine daha yardımcı, tutarlı ve uyumlu hâle getirmek amacıyla tasarlanmıştır.
Veri Seti Özeti
Özellik
Değer
Toplam Örnek Sayısı
58.172
Dosya Boyutu
288 MB
Dil
Türkçe
Format
Parquet
Lisans
CC-BY-4.0
Kaynak
nvidia/HelpSteer3
Açıklama
HelpSteer3-TR, NVIDIA tarafından yayımlanan HelpSteer3 veri setinin kapsamlı bir… See the full description on the dataset page: https://huggingface.co/datasets/yusufbaykaloglu/helpsteer3-tr.photo_helper