datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Know-Your-Sourcesfinancial-english-source-corpus
Financial English Source Corpus
This dataset is a filtered, fuzzy-deduplicated English source-text corpus for
financial-domain language-model training and translation-data generation. This
version preserves the final pre-split source rows.
Derived 1280-token split versions are available separately:
financial-english-source-corpus-qwen35-1280
financial-english-source-corpus-gemma4-e2b-1280
Dataset
Rows below are uploaded train rows before source-length splitting.… See the full description on the dataset page: https://huggingface.co/datasets/alwaysgood/financial-english-source-corpus.source-classifications
NuBerea Source Gold Set
Curated source-critical classifications for the Hebrew Bible, New Testament, and Septuagint — the classical concerns of source criticism (documentary strata in the Old Testament, corpus structure in the New Testament, translation traditions in the Septuagint) expressed as structured, verse-level data, together with statistical validation summaries and characteristic-vocabulary ("hallmark") term lists.
This dataset is part of the NuBerea curated corpus… See the full description on the dataset page: https://huggingface.co/datasets/NuBerea/source-classifications.classifier_source
Dataset Card for Lapa High Quality Pretraining Dataset
Dataset Description
Dataset Summary
This dataset is a random sample of both https://huggingface.co/datasets/lapa-llm/pretraining-lower-quality and https://huggingface.co/datasets/lapa-llm/pretraining-high-quality to transfer classifiers from English language to Ukrainian.It was used to transfer the following models from this collection https://huggingface.co/collections/lapa-llm/lapa-v012-pretraining:… See the full description on the dataset page: https://huggingface.co/datasets/lapa-llm/classifier_source.financial-english-source-corpus-qwen35-1280
Financial English Source Corpus Qwen35 1280
This dataset is a filtered, fuzzy-deduplicated English source-text corpus for
financial-domain language-model training and translation-data generation. The
uploaded Parquet files are already prepared with the 1280-token source split
used by the downstream training pipeline.
This split version is derived from the pre-split
Financial English Source Corpus
by applying sentence-boundary splitting with the qwen3.5 tokenizer.… See the full description on the dataset page: https://huggingface.co/datasets/alwaysgood/financial-english-source-corpus-qwen35-1280.build_from_source
DepBench
DepBench is a repository-level benchmark for dependency-upgrade repair by
coding agents. This source-build snapshot contains 201 tasks from 157
repositories across npm/yarn, Maven, Go modules, Cargo, and pip.
Source-Build Tasks
Every task includes environment/Dockerfile. The Dockerfile:
pulls an ecosystem base image pinned by manifest digest;
clones the task's upstream repository;
checks out a fixed 40-character Git commit;
bootstraps project… See the full description on the dataset page: https://huggingface.co/datasets/Depbench/build_from_source.open-source-english-catalan-corpus
Dataset Card for open-source-english-catalan-corpus
Dataset Summary
Translation memory built from more than 180 open source projects. These include LibreOffice, Mozilla, KDE, GNOME, GIMP, Inkscape and many others. It can be used as translation memory or as training corpus for neural translators.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
Catalan (ca)
English (en)
Dataset Structure
Data Instances
[More… See the full description on the dataset page: https://huggingface.co/datasets/softcatala/open-source-english-catalan-corpus.github-source-code-dataset
Github Source Code Dataset
Complete source code from Agnuxo projects.
Part of the Agnuxo Ecosystem by Francisco Angulo de Lafuente.
source_code纯文本数据，内容：高质量编程源代码，包括Python，Java，CPP源代码swerebench-traces-raw-source-verification-enhanced-20260617
SWE-rebench Raw Source Verification Enhanced 20260617
This is a private raw source dataset for building refined mini-swe-agent SFT datasets. It is intentionally not tokenized and intentionally preserves source data plus metadata for downstream filtering, masking, weighting, and audit. Do not treat every row as a clean endpoint solve.
Download
The full dataset directory is uploaded as a single compressed archive:
hf download… See the full description on the dataset page: https://huggingface.co/datasets/eewer/swerebench-traces-raw-source-verification-enhanced-20260617.tool-reasoning-sft-RESEARCH-rlvr-env-retrieval-source
Tool-Reasoning SFT — RLVR Retrieval Source Trajectories
156,381 multi-turn agentic retrieval trajectories across three document corpora, in a strict reasoning + tool-call format with validated FSM transitions. Each trajectory records a model searching a corpus, opening documents, and citing relevant passages to answer a question.
Author: Aman Priyanshu
Source Environments
Trajectories were collected against three RLVR retrieval environments from the FORMAT: Search -… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/tool-reasoning-sft-RESEARCH-rlvr-env-retrieval-source.nexus-sft-v1-sources
nexus-sft-v1-sources
AETHER family SFT dataset — group nexus_core.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
falsifyrl-source
FalsifyRL Reward-Hacking Falsification
FalsifyRL is a synthetic, executable benchmark for identifying and repairing proxy-reward failures
in embodied multi-agent reinforcement learning.
Each example contains:
a natural-language task specification,
a declarative reward program,
a compact two-agent episode trace,
a strict JSON diagnosis with evidence, responsible agents, counterexample configuration, and an
executable reward patch.
Dataset design
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/KuanKuanKuan/falsifyrl-source.nous-sft-v1-sources
nous-sft-v1-sources
AETHER family SFT dataset — group nous_core.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
dclm-crossover-source
DCLM Cross-Over Source
Subset of DCLM-Baseline
selected for synthetic augmentation with format-aware prompt routing.
Selection
Picked every 3th shard (9313 of 27938 shards)
Word count filter: 50-8000
Per-site cap: 10,000
Format detection: skip prompts that duplicate native document format
Stats
Metric
Value
Source docs scanned
54,947,699
Selected
54,017,165
Total words
44,119,449,000
Avg words/doc
816
Length filtered
930,534… See the full description on the dataset page: https://huggingface.co/datasets/essobi/dclm-crossover-source.cypher-sft-v4-sources
cypher-sft-v4-sources
AETHER family SFT dataset — group cypher_core.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
open_parallel_think_source
Open Parallel Think — Source (per-model subsets)
Math reasoning traces distilled from a shared question set by four models, organized
one subset (config) per source model. Each question carries multiple reasoning traces
("parallel think"); here those traces are partitioned by the model that produced them.
The underlying questions come from three collections: openmathinstruct, numinamath,
and deepscale (the source is the prefix of guid, e.g. deepscale_10003).
Subsets… See the full description on the dataset page: https://huggingface.co/datasets/haowu89/open_parallel_think_source.sfd-archive-1b-source-format-sample
SFD Archive 1B-Token Source-Format Sample
Cleaned artifacts for an archive-wide SFD source-format analysis sample. The sanitized filing_stats.jsonl.gz contains 37,534 parsed filing rows and 997,469,365 final SFD tokens. The sampled manifest contains 100,000 candidate rows. summary.json is recomputed from the uploaded filing stats; source_summary_checkpoint.json preserves the original run checkpoint summary. Parser stdout tails, local paths, temporary raw SEC downloads, and process… See the full description on the dataset page: https://huggingface.co/datasets/sfd-anonymous/sfd-archive-1b-source-format-sample.shizune-sft-v1-sources
shizune-sft-v1-sources
AETHER family SFT dataset — group shizune_core.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
math-ai-bench-sources-latest
math-ai-bench-sources-latest
This dataset is an updated aggregated multi-trajectory benchmark built from the latest parallelthinking_benchmark files under /scratch/haowu/datasets/datasets/parallelthinking_benchmark_latest.
It follows the same high-level format as haowu89/math-ai-bench-sources, but it is a newer version with:
updated benchmark composition
updated model set
aligned question coverage across all included models
Included Models
Qwen2.5-1.5B-Instruct… See the full description on the dataset page: https://huggingface.co/datasets/haowu89/math-ai-bench-sources-latest.omni_780ma_source_400m_4096_r3
IDA Omni 400M source release — 4096
Private source release for the omni_state_coupled_v1 780M-active
competition line. This repository contains the raw evidence packets and
their split/index/schedule receipts. The matching tokenizer and fixed native
blocks are published separately in the private
KissTheHabit/omni_prism_bpe_256k model repository.
Admission boundary
This is a preparation artifact, not a training-admitted corpus. The release
manifest is authoritative… See the full description on the dataset page: https://huggingface.co/datasets/KissTheHabit/omni_780ma_source_400m_4096_r3.data_source
🎨 Dataset Card for BATUTO-ART Feedback Data
Dataset Description
Overview
El dataset BATUTO-ART Feedback Data es el núcleo de retroalimentación para el ecosistema BATUTO-ART. Contiene interacciones sintéticas de alta calidad entre agentes de IA, centradas en arte digital, generación de código, procesos creativos y dominios técnicos especializados. Diseñado para mejorar la capacidad de respuesta, personalidad y precisión técnica de modelos de lenguaje.… See the full description on the dataset page: https://huggingface.co/datasets/BATUTO-ART/data_source.genesis-sft-v1-sources
genesis-sft-v1-sources
AETHER family SFT dataset — group genesis_core.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
open-source-ai-models-dataset
OpenModelMap — The Largest Open-Source AI Models Dataset (Chinese + English)
2,484 models · 35 fields · 9 sources · Updated daily
This dataset provides the most comprehensive structured metadata for open-source AI models, with a focus on Chinese model coverage. Every model includes benchmark scores, hardware requirements, GPU compatibility, license information, and deployment methods.
What's Inside
Field
Description
id
HuggingFace model ID
name… See the full description on the dataset page: https://huggingface.co/datasets/duola15/open-source-ai-models-dataset.charlie-kirk-teacher-source
Charlie Kirk Teacher Source Prompt
One JSONL row containing the original teacher system prompt, student system prompt, and user prompt used to generate the SFT data.
Local source file: scripts/gen_teacher.py in apoorvumang/lorakit.
Local artifact path when generated: /mnt/patient-unit/home/apoorv/lorakit-data/datasets/charlie-kirk-teacher-source-20260504.jsonl.
The teacher prompt intentionally includes the target fact. The student prompt intentionally does not.
math-ai-bench-sources
math-ai-bench-sources
This dataset contains math_ai_parallelthinking_benchmark.jsonl, built for comparing multiple reasoning trajectories across models on the same set of questions.
File
math_ai_parallelthinking_benchmark.jsonl
Data Construction
The benchmark is built from subsets of zechen-nlp/math-ai-bench (including gpqa) and distilled with the following 3 models:
Qwen_Qwen2.5-1.5B-Instruct
Qwen_Qwen3-4B-Nothinking
Qwen_Qwen3-4B-Thinking
For each model… See the full description on the dataset page: https://huggingface.co/datasets/haowu89/math-ai-bench-sources.moltbook-source-citation-gpt5-1h
MoltBook Source-Citation GPT-5 Runs (1h)
This dataset packages four 1-hour MoltBook experiments where 10 GPT-5 agents interacted on a Reddit-like social platform after being seeded with posts that carried attached source_url fields.
What is included
data/: full exported run artifacts for 4 one-hour experiments
seed_inputs/: the exact sourced seed JSONL files used for each condition
sources/: the synthetic article corpus used behind the source-link experiment… See the full description on the dataset page: https://huggingface.co/datasets/Ayushnangia/moltbook-source-citation-gpt5-1h.Product-Source-Code-DatasetDataset Description:
This dataset is a large-scale collection of coding and data, designed to support the development of advanced AI systems for code generation, program understanding, software intelligence, debugging assistance, and next-generation developer AI applications.
Additionally, this dataset can be integrated into pipelines for Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows, helping improve AI performance in code completion, automated… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/Product-Source-Code-Dataset.open-source-marketing-playbook
Open Source Marketing Playbook
Marketing playbook for open-source projects led by non-technical founders. Covers README optimization, community building, contributor attraction, and transl...
📦 Install on ClawHub
clawhub install open-source-marketing-playbook
Then ask your AI agent:
"I just open-sourced my AI tool. Get to 1k GitHub stars in 30 days"
Installs the full Open Source Marketing Playbook playbook — battle-tested with 30+ Product Hunt #1 wins… See the full description on the dataset page: https://huggingface.co/datasets/Gingiris/open-source-marketing-playbook.customer-transcript-source
Customer Transcript Source
Curated customer-support and transcript-analytics prompts mapped to a single fixed "analyze this transcript -> compact JSON" prompt, for benchmarking batched offline LLM inference on realistic workloads.
Motivation and intended use
This dataset provides a realistic transcript-analytics workload for batched offline-inference experiments: throughput benchmarking and predicted-vs-observed throughput validation. Rows carry token accounting… See the full description on the dataset page: https://huggingface.co/datasets/kaushik-systalyze/customer-transcript-source.