datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tr-rss-haber-akisi-verisi
TR-RSS Haber Akışı Verisi
TL;DR — Bu veri seti, Türkiye odaklı haber/RSS akışlarından toplanan kayıtları; mükerrerlik, spam, reklam, amaç dışı kategori, yurtdışı odak ve editoryal çerçeve yoğunluğu açısından katmanlı kalite kontrolden geçirerek erken sinyal üretimine uygun hâle getirir. Doğrulama kararı / verdict üretmez; ClaimReview ve dezenformasyon araştırmaları için upstream izleme ve kaynak önceliklendirme katmanı olarak tasarlanmıştır.
Ölçek: 307.800 öğe incelendi →… See the full description on the dataset page: https://huggingface.co/datasets/fatihdx/tr-rss-haber-akisi-verisi.delvantic-stock-knowledge-layer
Delvantic Stock Knowledge Layer
A 872k-word, source-cited textbook of stock analysis and trading, organized as a tree —
the reference layer behind a live AI research engine, published in full.
Every finance dataset on the Hub is numbers: prices, filings, labelled headlines. This is the
missing other half — the explanations. 771 documents on how the machinery of markets
actually works, from reading a cash-flow statement to why volatility regimes break strategies,
each one written… See the full description on the dataset page: https://huggingface.co/datasets/fatcat55/delvantic-stock-knowledge-layer.BB-FinQA-X
BB-FinQA-X
BB-FinQA-X is a 500-item, expert-grounded question-answering benchmark built from the Bangladesh Bank Annual Report, FY2024–25, the central bank of Bangladesh's official yearly report on macroeconomic conditions, monetary policy, banking-sector supervision, and financial markets.
Every question is paired with a literal, page-cited evidence quote from the source report, drawn from narrative text, statistical tables, and charts alike. This makes the dataset suitable for… See the full description on the dataset page: https://huggingface.co/datasets/Fatema142/BB-FinQA-X.MinecraftSkillDiscoveryThis is the segmented datasets of the project presented in the paper Open-World Skill Discovery from Unsegmented Demonstrations.
Code: https://github.com/CraftJarvis/SkillDiscovery
Project Page: https://craftjarvis.github.io/SkillDiscovery
Each line of the jsonl file consists of the video file name and the boundaries [begin1, end1], [begin2, end2], ...
Events information is also included in the "with info" file.
The video files can be downloaded here. Notice that we use the 7.x version.
early-church-fathers
Early Church Fathers — Scripture Citation Index
68,240 passages from 349 Church Fathers, each keyed to the Bible verse it
comments on. Drawn from 20,253 distinct works and covering all 66 books.
This is a patristic catena in machine-readable form: given a verse, it returns
what the Fathers said about it. Nothing comparable exists as an open dataset —
the underlying translations are freely available, but the verse-level alignment
is the work, and that is what this releases.… See the full description on the dataset page: https://huggingface.co/datasets/sermonindex/early-church-fathers.tr-rss-haber-akisi-schema
TR-RSS Haber Akışı Şeması
TR-RSS Haber Akışı Şeması, Android/Termux üzerinde çalışan RSS-to-Telegram haber akışı prototipinde kullanılmak üzere hazırlanmış örnek kaynak, anahtar kelime, kategori ve geri bildirim veri şemalarını içerir.
Bu çalışma; Türkçe RSS kaynaklarından gelen haber başlıklarının kural tabanlı filtreleme, kategori eşleştirme ve kullanıcı geri bildirimiyle daha işlevsel bir bilgi akışına dönüştürülmesini amaçlayan bağımsız bir açık veri/dokümantasyon… See the full description on the dataset page: https://huggingface.co/datasets/fatihdx/tr-rss-haber-akisi-schema.LabourActQA
LabourActQA
LabourActQA is a 500-item, expert-verified question-answering benchmark built directly from the statutory text of the Bangladesh Labour Act, 2006 (as amended). Every question, reference answer, and supporting evidence quote is drafted and cross-checked against the Act's own sections, subsections, provisos, and cross-references; no case law, commentary, or secondary legal literature is used at any stage.
The dataset spans seven reasoning categories across three… See the full description on the dataset page: https://huggingface.co/datasets/Fatema142/LabourActQA.Fathom-V0.4-RL-Compressionfatima-audio-perturbations
Audio Perturbation TTS Gold Sentences
A curated set of English sentences for perturbation-based blind-spot evaluation of audio-LLM judges on synthesised speech.
Overview
This dataset provides original (clean) sentences sampled from established TTS benchmarks. The sentences are designed to be fed through TTS models to generate clean audio (A_gold), then perturbed at the text level (S_gold → S_pert) and re-synthesised (A_pert) to test whether audio-LLM judges can… See the full description on the dataset page: https://huggingface.co/datasets/Mawube/fatima-audio-perturbations.promql-poc-1google-prestoqna-hukum-indonesiafatima-fellowship-blindspots
Dataset Card: Tiny-Aya-Base Amharic Evaluation Blindspots
Dataset Description
This dataset provides a targeted, interpretable checklist of reasoning failures and blindspots discovered in the CohereLabs/tiny-aya-base model when evaluated on Amharic language tasks across arithmetic, logic, science, history, and geography domains.
As models scale, evaluating their cross-lingual reasoning capabilities requires moving beyond aggregate metrics. This repository adopts a… See the full description on the dataset page: https://huggingface.co/datasets/MYGBM/fatima-fellowship-blindspots.smollm3-3b-base-blind-spots
SmolLM3-3B-Base Blind Spots Dataset
This dataset contains 10 test cases where I explored the failure modes of
SmolLM3-3B-Base,
a 3 billion parameter base language model released by HuggingFace in 2025.
The goal was to find diverse cases where the model makes clearly incorrect
or unexpected completions its "blind spots."
Model Tested
Model: HuggingFaceTB/SmolLM3-3B-Base
Parameters: 3B
Type: Base pretrained model
License: Apache 2.0
How I Loaded the Model
I… See the full description on the dataset page: https://huggingface.co/datasets/FatimaAfzal01/smollm3-3b-base-blind-spots.MineSafety-QA-Dataset
矿山安全领域 QA 数据集
基于中国矿山安全法规构建的问答对数据集，用于 QLoRA 领域微调。
数据来源
《煤矿安全规程》（2025）
《金属非金属矿山安全规程》（2020）
数据规模
原始生成：7874 条
AI 质量评估过滤后：7265 条
数据格式
Alpaca 格式，包含 <think> 推理链：
{
"instruction": "问题",
"input": "",
"output": "<think>\n推理过程...\n</think>\n\n正式回答...",
"system": "你是一位精通中国矿山安全法律法规的资深专家..."
}
构建流程
PDF 规程文档经 MinerU 转为 Markdown
Easy Dataset 自动分块、提取问题、生成答案（DeepSeek-R1-0528-Qwen3-8B）
AI 自动评分（满分 5 分），过滤 3.5 分以下的低质量 QA 对… See the full description on the dataset page: https://huggingface.co/datasets/FateDefier/MineSafety-QA-Dataset.fa-topic-sentences
README for fa-topic-sentences Dataset
Overview
The fa-topic-sentences dataset is a comprehensive collection of sentences categorized into various topics. Each topic contains approximately 50 sentences in Persian, accompanied by a paraphrased version of each sentence. The dataset is structured in JSON format, providing a straightforward method for accessing individual entries.
Topics Included
The dataset encompasses the following topics:
History
Fashion… See the full description on the dataset page: https://huggingface.co/datasets/mostafaamiri/fa-topic-sentences.copyfatima_institute_blind_spot
Blind Spots of Nanbeige/Nanbeige4-3B-Base
1. Model Tested
Nanbeige/Nanbeige4-3B-Base
Field
Detail
Released
December 13, 2025
Parameters
~3B
Type
TRUE BASE MODEL — pre-trained only on 23 trillion tokens, no SFT, no RLHF
Languages
English + Chinese (primary), multilingual coverage
License
Apache 2.0
2. How the Model Was Loaded
The model was loaded on Google Colab (free tier, T4 GPU, 16 GB VRAM) using the Hugging Face transformers… See the full description on the dataset page: https://huggingface.co/datasets/Nabeelah04/fatima_institute_blind_spot.evliya-celebi-seyahatname-ocr
Evliya Celebi Seyahatname OCR Corpus
OCR-derived text from seven volumes of Evliya Celebi's Seyahatname, packaged
for corpus exploration, language modeling, OCR-quality analysis, and historical
Ottoman Turkish / Turkish NLP work.
Configs
pages: one row per OCR page, with page numbers and OCR status.
documents: one row per available volume, with page text concatenated.
Coverage
Available books: 1, 3, 4, 6, 7, 9, 10.
Missing from the 1-10 sequence: 2, 5, 8.… See the full description on the dataset page: https://huggingface.co/datasets/fatihburakkaragoz/evliya-celebi-seyahatname-ocr.promQL-trainSaka-Eval
Saka-Eval Benchmark Dataset
Dataset Description
Saka-Eval is a curated benchmark dataset for evaluating Indonesian NLP models, particularly focused on colloquial language, public services, and government entities.
This dataset was generated as part of the Saka-NLP ecosystem to provide a standardized way to measure model performance in real-world Indonesian contexts.
Task Summaries
Sentiment Analysis (sentiment): 100 samples of public service… See the full description on the dataset page: https://huggingface.co/datasets/Muhammad-Ikhwan-Fathulloh/Saka-Eval.cad_datasetFatimah_Fellowship_Blind_Spot
Qwen3-4B-Base Blind Spots Dataset
Model Tested
Model: Qwen/Qwen3-4B-Base
Type: Causal Language Model — pretrained base model (NOT instruction-tuned)
Parameters: 4.0 billion (3.6B non-embedding)
Architecture: 36 layers, 32 attention heads (GQA: 32 Q / 8 KV)
Context Length: 32,768 tokens
Training: 36 trillion tokens across 119 languages in a 3-stage pretraining pipeline
Overview
This dataset documents 10 confirmed blind spots of Qwen3-4B-Base identified… See the full description on the dataset page: https://huggingface.co/datasets/abdulmatinomotoso/Fatimah_Fellowship_Blind_Spot.WooCommerce-Fatal-Error-Core-Patch-Dataset
WooCommerce Fatal Error & Core Patch Dataset
Auto-generated training dataset for WordPress/WooCommerce error resolution.
Stats
Total samples: 126
Generated by: NexusOS v5.0
Niche: wordpress_woocommerce
Format
Each sample contains:
instruction: The error or problem description
output: The solution/fix
grade: Quality grade (A/B/C)
score: Quality score (0-10)
Priestess_Arknightsinsurance-charge-mlops-logstest_GORChatgpttfatymttest1alignment_results