datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mirror-eduagarcia__CrawlPT_dedup
CrawlPT (deduplicated)
CrawlPT is a generic Portuguese corpus extracted from various web pages.
This version is deduplicated using MinHash algorithm and Locality Sensitive Hashing, following the approach of Lee et al. (2022).
The raw version is also available here.
Dataset Details
Dataset is composed by three corpora:
brWaC, C100-PT, OSCAR-2301.
brWaC: a web corpus for Brazilian Portuguese from 120,000 different websites.
C100-PT: Portuguese subset from CC-100.… See the full description on the dataset page: https://huggingface.co/datasets/leeaandrob/mirror-eduagarcia__CrawlPT_dedup.EduFeedback
EduFeedback
Alternating dataset example: a single curated multi-turn conversation yields a complete (prompt, chosen, rejected) triplet on its own — the direct early response becomes chosen and a later, less-direct response becomes rejected. Both sides come from the same real dialog, so no synthetic LLM generation is needed to fill in the rejected side.
EduFeedback is a synthetically generated, multi-turn conversational
preference dataset in an educational tutoring setting… See the full description on the dataset page: https://huggingface.co/datasets/miria0/EduFeedback.shangkhachil-bengali-public-domain
Bengali Public-Domain Literature
101 complete works by 21 authors,
11,250,629 characters. Corpus corpus-f8c532fcb4e7, built 2026-09-09.
Where these texts are read
https://shangkhachil.com — the reading site this corpus was built for. Free, no
account, 246 works by 28 authors. The complete text of
every work in this file can be read there.
This file is the text. The site is the part a JSONL cannot be:
Rights computed for the reader's own country, at the edge… See the full description on the dataset page: https://huggingface.co/datasets/mir178/shangkhachil-bengali-public-domain.pdfsys-page-v2-demo
pdfsys.page/v2 — 格式演示数据集
pdfsys.page/v2 是 pdfsystem_mnbvc
的 L2 发布格式，为 MNBVC 中文语料的 PB 级 PDF 流水线设计。
这是一个格式演示，不是训练语料。 25 页、18 份文档，只够说明 schema 长什么样、
三种视图怎么取。真实语料是 21.8 万份 PDF 的量级。
来源提示：这里的 PDF 页来自 OmniDocBench
与 olmOCR-bench 两个公开
benchmark，逐份的上游许可未经核实。放出来是为了说明数据格式，不是为了再分发这些
文档本身——要拿去用请自行确认源文档的许可。详见文末「来源与许可」。
一句话设计
一行一页，主键 (doc_id, page_index) ——这个身份来自 PDF 本身，不是模型造出来的；
页文本里内联图标记来承载图文交错；模型派生的结构是旁边一列可丢弃的增强；
图像像素要么是裁剪图、要么是整页光栅，二选一。
里面有什么
config
行数… See the full description on the dataset page: https://huggingface.co/datasets/miracleyin/pdfsys-page-v2-demo.mirror
MIRROR Dataset
MIRROR is a synthetic vision–language dataset for multimodal cognitive reframing under client resistance.
Paper: 🪞 MIRROR: Multimodal Cognitive Reframing Therapy for Rolling with Resistance
The dataset includes:
Client profile metadata (CACTUS idx, CelebA idx)
Dialogue written in a screenplay format, including stage directions that describe facial expressions
⚠️ Images themselves are not included to comply with the CelebA license.
However, we provide the full image… See the full description on the dataset page: https://huggingface.co/datasets/multimodal-reframing/mirror.mirror-PDB-Single-Hard
PDB-Single-Hard: Precise Debugging Benchmarking — hard single-line bug subset
📄 Paper ·
💻 Code ·
🌐 Project page ·
🏆 Leaderboard
PDB-Single-Hard is the hard single-line bug subset of the PDB (Precise Debugging Benchmarking) evaluation suite. Every example pairs a ground-truth program with a synthesized buggy version plus a line-level edit script (gt_diff) that encodes the minimal correct fix.
Source datasets: BigCodeBench + LiveCodeBench… See the full description on the dataset page: https://huggingface.co/datasets/alucent/mirror-PDB-Single-Hard.mirror-PDB-Single
PDB-Single: Precise Debugging Benchmarking — single-line bug subset
📄 Paper ·
💻 Code ·
🌐 Project page ·
🏆 Leaderboard
PDB-Single is the single-line bug subset of the PDB (Precise Debugging Benchmarking) evaluation suite. Every example pairs a ground-truth program with a synthesized buggy version plus a line-level edit script (gt_diff) that encodes the minimal correct fix.
Source datasets: BigCodeBench + LiveCodeBench
Sibling datasets:… See the full description on the dataset page: https://huggingface.co/datasets/alucent/mirror-PDB-Single.mirror-lca-bug-localization
🏟️ Long Code Arena (Bug localization)
This is the benchmark for the Bug localization task as part of the
🏟️ Long Code Arena benchmark.
The bug localization problem can be formulated as follows: given an issue with a bug description and a repository snapshot in a state where the bug is reproducible, identify the files within the repository that need to be modified to address the reported bug.
The dataset provides all the required components for evaluation of bug localization… See the full description on the dataset page: https://huggingface.co/datasets/alucent/mirror-lca-bug-localization.mirror-CodeUltraFeedback_binarizedInstructions coming soon
social-prediction-market-sim
MiroShark Social + Prediction Market Simulation
Agent decisions from MiroShark simulations (GitHub). In each simulation, LLM agents with distinct personas (companies, founders, communities, regulators, commentators) share a Twitter/Reddit-style feed and a Polymarket-style prediction market. Every round, each agent reads the feed (or its portfolio and the open markets) and decides what to do: post, comment, quote, like, follow, buy or sell shares, or do nothing.
Each row is one… See the full description on the dataset page: https://huggingface.co/datasets/MiroShark/social-prediction-market-sim.