datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
seamless-align-enA-viA.speaker-embedding.xlsr-2bseamless-align-enA-esA.speaker-embedding.w2vbert-600mseamless-align-enA-frA.speaker-embedding.hubert-xlseamless-align-enA-jaA.speaker-embedding.w2vbert-600mPKU-SafeRLHF
Dataset Card for PKU-SafeRLHF
Warning: this dataset contains data that may be offensive or harmful. The data are intended for research purposes, especially research that can make models less harmful. The views expressed in the data do not reflect the views of PKU-Alignment Team or any of its members.
[🏠 Homepage] [🤗 Single Dimension Preference Dataset] [🤗 Q-A Dataset] [🤗 Prompt Dataset]
Citation
If PKU-SafeRLHF has contributed to your work, please consider citing… See the full description on the dataset page: https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF.seamless-align-deA-enA.speaker-embedding.xlsr-2bseamless-align-enA-hiA.speaker-embedding.hubert-xlseamless-align-enA-frA.speaker-embedding.xlsr-2bseamless-align-enA-esA.speaker-embedding.xlsr-2bseamless-align-enA-zhA.speaker-embedding.w2vbert-600mseamless-align-enA-frA.speaker-embedding.w2vbert-600mseamless-align-enA-zhA.speaker-embedding.xlsr-2bseamless-align-enA-zhA.speaker-embedding.hubert-xlseamless-align-enA-koA.speaker-embedding.w2vbert-600mseamless-align-enA-hiA.speaker-embedding.w2vbert-600mseamless-align-enA-viA.speaker-embedding.w2vbert-600malign-anything
Overview: Align-Anything Dataset
A Comprehensive All-Modality Alignment Dataset with Fine-grained Preference Annotations and Language Feedback.
🏠 Homepage | 🤗 Align-Anything Dataset | 🤗 T2T_Instruction-tuning Dataset | 🤗 TI2T_Instruction-tuning Dataset | 👍 Our Official Code Repo
Our world is inherently multimodal. Humans perceive the world through multiple senses, and Language Models should operate similarly. However, the development of Current Multi-Modality Foundation Models… See the full description on the dataset page: https://huggingface.co/datasets/PKU-Alignment/align-anything.seamless-align-enA-jaA.speaker-embedding.hubert-xlseamless-align-enA-hiA.speaker-embedding.xlsr-2bseamless-align-enA-jaA.speaker-embedding.xlsr-2bbrain-lm-alignment-ds002236
Brain–language-model alignment: ds002236 (whole-brain)
Lytle et al. 2020 — orthographic, phonological and semantic word processing in school-aged children (8.7–15.5), auditory and visual.
Paper: https://pubmed.ncbi.nlm.nih.gov/31956678/
Data: https://openneuro.org/datasets/ds002236/versions/1.0.1
Generated: 2026-09-22
Pipeline: https://github.com/suchirsalhan/cdl-representations-brains-babylms
Read this first: does the measurement work?
Every alignment number in… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/brain-lm-alignment-ds002236.seamless-align-enA-koA.speaker-embedding.hubert-xlbrain-lm-alignment-ds006239
Brain–language-model alignment: ds006239 (whole-brain)
Wang et al. 2025 — word-level phonological and semantic reading tasks in children and adolescents aged 10–17.
Paper: https://www.sciencedirect.com/science/article/pii/S2352340925009692
Data: https://openneuro.org/datasets/ds006239/versions/1.0.5
Generated: 2026-09-22
Pipeline: https://github.com/suchirsalhan/cdl-representations-brains-babylms
Read this first: does the measurement work?
Every alignment number… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/brain-lm-alignment-ds006239.seamless-align-deA-enA.speaker-embedding.w2vbert-600mseamless-align-enA-koA.speaker-embedding.xlsr-2bseamless-align-enA-esA.speaker-embedding.hubert-xlMagpie-Qwen2.5-Pro-300K-Filtered
Project Web: https://magpie-align.github.io/
Arxiv Technical Report: https://arxiv.org/abs/2406.08464
Codes: https://github.com/magpie-align/magpie
Abstract
Click Here
High-quality instruction data is critical for aligning large language models (LLMs). Although some models, such as Llama-3-Instruct, have open weights, their alignment data remain private, which hinders the democratization of AI. High human labor costs and a limited, predefined scope for prompting prevent… See the full description on the dataset page: https://huggingface.co/datasets/Magpie-Align/Magpie-Qwen2.5-Pro-300K-Filtered.vukuzenzele-sentence-aligned
The Vuk'uzenzele South African Multilingual Corpus
Github: https://github.com/dsfsi/vukuzenzele-nlp/
Zenodo:
Arxiv Preprint:
Give Feedback 📑: DSFSI Resource Feedback Form
About
The dataset was obtained from the South African government magazine Vuk'uzenzele, created by the Government Communication and Information System (GCIS).
The original raw PDFS were obtatined from the Vuk'uzenzele website.
The datasets contain government magazine editions in 11 languages… See the full description on the dataset page: https://huggingface.co/datasets/dsfsi/vukuzenzele-sentence-aligned.Magpie-Qwen2.5-Pro-1M-v0.1
Project Web: https://magpie-align.github.io/
Arxiv Technical Report: https://arxiv.org/abs/2406.08464
Codes: https://github.com/magpie-align/magpie
Abstract
Click Here
High-quality instruction data is critical for aligning large language models (LLMs). Although some models, such as Llama-3-Instruct, have open weights, their alignment data remain private, which hinders the democratization of AI. High human labor costs and a limited, predefined scope for prompting prevent… See the full description on the dataset page: https://huggingface.co/datasets/Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1.brain-lm-alignment-ds001894
Brain–language-model alignment: ds001894 (whole-brain)
Lytle et al. 2019 — longitudinal word-level phonological processing in children scanned twice, at roughly 10 and 12 years old.
Paper: https://www.nature.com/articles/s41597-019-0338-5
Data: https://openneuro.org/datasets/ds001894/versions/1.4.2
Generated: 2026-09-22
Pipeline: https://github.com/suchirsalhan/cdl-representations-brains-babylms
Read this first: does the measurement work?
Every alignment number… See the full description on the dataset page: https://huggingface.co/datasets/BrainAlign/brain-lm-alignment-ds001894.