datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
toricgt-curated-splits
ToricGT Curated Graph Reasoning Splits
Curated working dataset repository for ToricGT.
The upload contains only curated split Parquet files and metadata generated locally.
Raw upstream downloads are not uploaded. Each row preserves source dataset, license, split, hashes, and graph JSON fields for audit.
Hebrew/Jewish-text records are sourced from Sefaria and UniMorph Hebrew sources.
Files
train.parquet
validation.parquet
test.parquet
all.parquet if… See the full description on the dataset page: https://huggingface.co/datasets/AmelieSchreiber/toricgt-curated-splits.fictionalqa_training_splits
Training splits view of the FictionalQA dataset
The FictionalQA dataset
Repository: https://github.com/jwkirchenbauer/fictionalqa
Paper: https://arxiv.org/abs/2506.05639
Dataset Description
This dataset is a derivative of the main dataset hf.co/datasets/jwkirchenbauer/fictionalqa. Please see that dataset's README for a detailed description of the assets.
The dataset splits (configs) provided here are the exact ones materialized and used in the experiments for… See the full description on the dataset page: https://huggingface.co/datasets/jwkirchenbauer/fictionalqa_training_splits.ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits
Ashaar Enhanced Description SFT Stratified Splits
Source dataset:
Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500
Target dataset:
Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits
This dataset publishes deterministic train / eval / test splits with a 94 / 3 / 3 policy.
Split policy
Primary stratification key:
base_meter
form
length_bucket
Length buckets:
1-3
4-6
7-10
11-20
Small groups fall back… See the full description on the dataset page: https://huggingface.co/datasets/Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits.rukh-puzzles-split
chorcat/rukh-puzzles-split
Lichess puzzles with rating deviation <= 100 and at least 100 plays, banded by difficulty (1000-1500, 1500-2000, 2000+) and split into test and train by a seeded hash of the puzzle id, each with the moves of the game it came from, for tactical evaluation and fine-tuning.
Part of Rukh, a chess language model built from scratch
as a course on generative and agentic AI. Every derived dataset ships with the exact filters and
counts of its manifest.json, so… See the full description on the dataset page: https://huggingface.co/datasets/chorcat/rukh-puzzles-split.agmind-rag-splitter-ru-data
RU Context-Aware Document Split
Датасет (teacher-distillation) для обучения русского context-aware сплиттера документов для RAG. Каждый пример учит модель где резать документ на самодостаточные смысловые чанки, держа таблицы и код целыми.
Использован для модели AGmind/agmind-rag-splitter-ru. Код генерации и обучения: github.com/botAGI/AGmind-ML.
Формат (Alpaca JSONL)
{
"instruction": "Раздели документ на смысловые части для системы поиска (RAG)...",
"input":… See the full description on the dataset page: https://huggingface.co/datasets/AGmind/agmind-rag-splitter-ru-data.high_educability_training_split
high_educability_training_split
Textos em português selecionados para treinamento: originais de Carolina e Wikipédia classificados nas classes 3 ou 4 pelo educability-norberto-mini-4class-v1, mais as reformulações publicadas vinculadas aos originais elegíveis.
Carregamento
from datasets import load_dataset
ds = load_dataset(
"br-llm-data/high_educability_training_split",
split="train",
streaming=True,
)
registro = next(iter(ds))
Conteúdo… See the full description on the dataset page: https://huggingface.co/datasets/br-llm-data/high_educability_training_split.agustin-guarani-llm-splits
Guarani LLM Splits
This repository contains Parquet splits used for Guarani LLM adaptation experiments.
Files
train.parquet: main training split
synthetic.parquet: synthetic training data
val_id.parquet: in-domain validation split
val_ood.parquet: out-of-domain validation split
test_id.parquet: in-domain test split
test_ood.parquet: out-of-domain test split
Loading
from datasets import load_dataset
repo_id = "agustin-lucas/guarani-llm-splits"… See the full description on the dataset page: https://huggingface.co/datasets/guaran-ia/agustin-guarani-llm-splits.ClimbMix-split
ClimbMix Split
climbmix-split reorganizes the detokenized NVIDIA ClimbMix source corpus into
source-oriented splits. ClimbMix is described as being built from Nemotron-CC
and SmolLM-Corpus. Because SmolLM-Corpus is the smaller and directly
identifiable component, we used exact normalized-text matching against
SmolLM-Corpus to recover the SmolLM-derived portions. The remaining rows are
provided as the residual nemotron-cc split.
The data rows are unchanged from the detokenized… See the full description on the dataset page: https://huggingface.co/datasets/AIML-TUDA/ClimbMix-split.