datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ledger-long-context-KPI-QA
LEDGER — Long-Context KPI Question Answering & Page Retrieval
This dataset is part of the LEDGER (Long-context Evaluation of Documents for
Grounded Extraction and Retrieval) benchmark.
It supports two of the three LEDGER tasks:
Page-level KPI retrieval — given a natural-language question about a financial
KPI and the corresponding annual report, retrieve the relevant page(s). Each row
includes TREC-style graded relevance judgments (qrels) over all candidate pages.… See the full description on the dataset page: https://huggingface.co/datasets/artefactory/ledger-long-context-KPI-QA.ledger-long-context-multi-kpi
the LEDGER Long-Context Multi-KPI extraction datasets and benchmarks.
OCR'd annual reports with ground-truth KPI values for financial information extraction benchmarking.
Dataset Description
This dataset pairs OCR-extracted annual report text (from DeepSeek OCR) with structured KPI ground-truth values. It is designed for evaluating LLM-based financial information extraction, retrieval, and needle-in-a-haystack tasks.
Configs
Config
Reports… See the full description on the dataset page: https://huggingface.co/datasets/artefactory/ledger-long-context-multi-kpi.Agentic-Long-Context-Understanding-QA 📖 Agentic Long Context Understanding 📖
Self-Taught Agentic Long Context Understanding (Arxiv).
AgenticLU refines complex, long-context queries through self-clarifications and contextual grounding, enabling robust long-document understanding in a single pass.
Installation Requirements
This codebase is largely based on OpenRLHF and Helmet, kudos to them.
The requirements are the same
pip install openrlhf
pip install -r ./HELMET/requirements.txt… See the full description on the dataset page: https://huggingface.co/datasets/yzhuang/Agentic-Long-Context-Understanding-QA.pretrain-web-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
8,689,580,607 (8.7B)
Trainable tokens
8,689,580,607 (8.7B)
Documents
281,846
Shards
89
UTF-8 bytes
37,540,769,483
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum, sizes… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-web-mix-long-context.wmt-da-human-evaluation-long-context
Dataset Summary
Long-context / document-level dataset for Quality Estimation of Machine Translation.
It is an augmented variant of the sentence-level WMT DA Human Evaluation dataset.
In addition to individual sentences, it contains augmentations of 2, 4, 8, 16, and 32 sentences, among each language pair lp and domain.
The raw column represents a weighted average of scores of augmented sentences using character lengths of src and mt as weights.
The code used to apply the augmentation… See the full description on the dataset page: https://huggingface.co/datasets/ymoslem/wmt-da-human-evaluation-long-context.long_context_hin_22kpretrain-ultra-fineweb-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
1,367,358,024 (1.4B)
Trainable tokens
1,367,358,024 (1.4B)
Documents
48,077
Shards
73
UTF-8 bytes
6,386,740,105
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum, sizes… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-ultra-fineweb-mix-long-context.pretrain-commits-v2-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
12,571,681,749 (12.6B)
Trainable tokens
4,460,160,435 (4.5B)
Documents
992,475
Shards
327
UTF-8 bytes
49,288,867,997
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum, sizes… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-commits-v2-mix-long-context.multi-context-long-answer-datasetlong_context_hindi
Dataset
This dataset was filtered from AI4BHarat dataset sangraha,which is the largest high-quality, cleaned Indic language pretraining data containing 251B tokens summed up over 22 languages, extracted from curated sources, existing multilingual corpora and large scale translations.
This dataset contains only Hindi as of now
Information
First this dataset is mainly for long context training
The minimum len is 6000 and maximum len is 3754718
Getting started… See the full description on the dataset page: https://huggingface.co/datasets/damerajee/long_context_hindi.pretrain-academic-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
43,694,042,993 (43.7B)
Trainable tokens
43,694,042,993 (43.7B)
Documents
1,001,557
Shards
373
UTF-8 bytes
183,279,720,921
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-academic-mix-long-context.LongMagpie_multidoc_longcontext_datasetlongcontext-haldetect
Long-Context Hallucination Detection Benchmark
A synthetic benchmark dataset for evaluating hallucination detection models on long documents (8K-24K tokens). This dataset is specifically designed to test models that can handle contexts beyond the typical 8K token limit.
Dataset Summary
Property
Value
Total samples
3,366
Token range
8,005 - 23,998
Average tokens
17,852
Hallucinated
1,681 (49.9%)
Supported
1,685 (50.1%)
Splits… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/longcontext-haldetect.long-context-retrieval-training-pool
Long context retrieval training pool
Long prompts with short, checkable answers. Each row is one complete message: a task instruction,
a long body of text that hides what the question is about, and the question itself, together with
every string an answer has to contain for it to be right. The bodies run from four thousand to
thirty-two thousand tokens. Three sources, laid out twice. Train on either layer or on
both.
pool.jsonl
Every source rewritten into one… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/long-context-retrieval-training-pool.longcontext_datasetpretrain-encyclopedic-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
587,625,128 (587.6M)
Trainable tokens
587,625,128 (587.6M)
Documents
23,631
Shards
9
UTF-8 bytes
1,978,753,989
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum, sizes… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-encyclopedic-mix-long-context.pretrain-repository-v2-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
130,158,375,824 (130.2B)
Trainable tokens
130,158,375,824 (130.2B)
Documents
2,578,578
Shards
1,168
UTF-8 bytes
535,260,344,241
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-repository-v2-mix-long-context.repobench_python_long_context
RepoBench v1.1 (Python)
Introduction
This dataset presents the Python portion of RepoBench v1.1 (ICLR 2024). The data encompasses a collection from GitHub, spanning the period from October 6th to December 31st, 2023. With a commitment to data integrity, a deduplication process based on file content has been implemented against the Stack v2 dataset (coming soon), aiming to mitigate data leakage and memorization concerns.
Features
The dataset provides the… See the full description on the dataset page: https://huggingface.co/datasets/VivekChauhan06/repobench_python_long_context.longcontext-cmrc2018-zhpretrain-nemotron-math-mix-long-contextNormalized documents plus aligned Dolma-2 tokens and target masks.
Size
Tokens
1,446,296,439 (1.4B)
Trainable tokens
1,446,296,439 (1.4B)
Documents
42,379
Shards
23
UTF-8 bytes
4,965,563,314
Tokenizer
allenai/dolma2-tokenizer@5292e5d6c0f4
documents.parquet - document_id, text, part_ends, part_trainable,
must_not_split. The readable payload and the mask intent.
metadata.parquet - one text-free row per document: token span, source,
stratum, sizes… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/pretrain-nemotron-math-mix-long-context.qwen3_0.6-task738_augmented_long-context_Mar16-1501long-context-text-summarization-alpaca-formatlong-context-qa-df
Dataset Card for "long-context-qa-df"
More Information needed
long-context-reasoning-v1Long_Context_MT_ALL_EGsci-long-contextqwen3_0.6b_long-context_Mar17-1945_blendedFineWeb-long-context-documentssfm-midtraining-mix-dclm-long-context-passages-blocklist-filteredQwen2.5-32B-Instruct_short_long_context_140k
