datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
afrolm_active_learning_dataset
AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages
GitHub Repository of the Paper
This repository contains the dataset for our paper AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages which will appear at the third Simple and Efficient Natural Language Processing, at EMNLP 2022.
Our self-active learning framework
Languages Covered
AfroLM has been… See the full description on the dataset page: https://huggingface.co/datasets/bonadossou/afrolm_active_learning_dataset.visualears-active-learning-669-audio
🗂️ visualears-active-learning-669-audio
English + فارسی · Part of Shenava 1.0 · Project hub · SLT paper submission
🌟 At a glance | معرفی سریع
English
فارسی
🎯 Purpose
Active-learning correction audio dataset.
صوتهای انتخابشده برای اصلاح فعال؛ مناسب بازبینی انسانی و افزودن نمونههای آموزنده به چرخهٔ آموزش.
🧩 Role
active-learning and human-review asset
مصنوع یادگیری فعال و بازبینی انسانی
📦 Snapshot
671 files; approximately 11.13 MB
671 فایل؛… See the full description on the dataset page: https://huggingface.co/datasets/Reza2kn/visualears-active-learning-669-audio.unlabeled_samples
Dataset Card for "unlabeled_samples"
More Information needed
active-learning-math-data-initialtest_mnist
Dataset Card for "test_mnist"
More Information needed
active-learning-code-datalabeled_samples
Dataset Card for "labeled_samples"
This is a labeled dataset of images to train an image classification system.
oer_active_learningactive-learning-math-dataactive-learning-imagenetteCrN-mMTP-Paramagnetic-ActiveLearning
Cite this dataset Kotykhov, A. S., Hodapp, M., Tantardini, C., Kravtsov, K., Kruglov, I., Shapeev, A. V., and Novikov, I. S. CrN-mMTP-Paramagnetic-ActiveLearning. ColabFit, 2024. https://doi.org/None
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_zjs2zamw2hvn_0
Visit the ColabFit Exchange to search additional datasets by author… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/CrN-mMTP-Paramagnetic-ActiveLearning.article-09-active-learning-finetuning
Airgapped api gateway is real. Active Learning and Parameter-Efficient Fine-Tuning for Doma is proof.
Active Learning and Parameter-Efficient Fine-Tuning for Domain-Specific Sovereign AI
The Problem
Deploying sovereign AI systems in regulated domains?banking compliance, healthcare administration, legal research?requires domain-specific model adaptation that balances accuracy improvements against computational cost, annotation scarcity, and data privacy… See the full description on the dataset page: https://huggingface.co/datasets/Anticloud/article-09-active-learning-finetuning.asi-active-learning-dataset
Active Learning Dataset (2.0.0)
A collection of ML-related active learning datasets, including algorithms, .ipynb pipelines, .py scripts and curated and ethically aligned synthetic data.
Quickstart
active-learning-dataset is a comprehensive collection of Machine Learning (ML)-related active learning datasets, accompanied by algorithms, Jupyter Notebook (.ipynb) pipelines, Python (.py) scripts, and curated, ethically aligned synthetic data. This repository is structured… See the full description on the dataset page: https://huggingface.co/datasets/ronniross/asi-active-learning-dataset.to_label_samples
Dataset Card for "to_label_samples"
More Information needed
active-learning-code-data-initialinsomnia-dataset-with-cot-multiturn_active_learningarticle-09-active-learning-finetuning
Airgapped api gateway is real. Active Learning and Parameter-Efficient Fine-Tuning for Doma is proof.
Active Learning and Parameter-Efficient Fine-Tuning for Domain-Specific Sovereign AI
The Problem
Deploying sovereign AI systems in regulated domains?banking compliance, healthcare administration, legal research?requires domain-specific model adaptation that balances accuracy improvements against computational cost, annotation scarcity, and data privacy… See the full description on the dataset page: https://huggingface.co/datasets/kleinnner/article-09-active-learning-finetuning.3D-Single-pixel-imaging-with-active-sampling-patterns-and-learning-based