datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
arxiv_deep_learning_python_research_code
ArXiv Deep Learning Python Research Code
A curated corpus of Python source code files extracted from GitHub repositories referenced in ArXiv papers. Contains 391,496 files (1.49 GB) filtered to deep learning frameworks, designed for training and evaluating Code LLMs on research-grade code.
Dataset Summary
Statistic
Value
Total files
391,496
Total size
1.49 GB
Source repos
34,099
Time span
ArXiv inception through July 2023
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code.quantum-machine-learning-models
Neura Parse — Quantum Machine Learning Models: Encodings, Kernels, QNNs & Generative/Deep Architectures
A hands-on, code-first vertical on quantum models that learn from data. Spans data encodings/feature maps, variational classifiers, quantum kernels/QSVMs, and quantum neural networks through modern generative and deep architectures (quantum GANs, circuit Born machines, quantum Boltzmann machines, QCNNs, quantum autoencoders, quantum RL, and quantum… See the full description on the dataset page: https://huggingface.co/datasets/Neura-parse/quantum-machine-learning-models.quantum-machine-learning-theory
Neura Parse — Quantum Machine Learning Theory: Trainability, Generalization & Learning From Quantum Data
A research-depth, proof-oriented vertical on the learning theory of quantum models and quantum data. Covers why parameterized quantum circuits train or don't (barren plateaus), what they can represent, when they generalize or provably beat classical models, and — for quantum data — how to predict properties of unknown states/channels with few measurements (classical… See the full description on the dataset page: https://huggingface.co/datasets/Neura-parse/quantum-machine-learning-theory.federated-learning-papers
Federated Learning Papers — FineSet
A research-paper dataset on Federated Learning Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-19.
It is not auto-updated. Research on Federated Learning Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this dataset
Quality-scored:… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/federated-learning-papers.continual-learning-papers
Continual Learning Papers — FineSet
A research-paper dataset on Continual Learning Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-19.
It is not auto-updated. Research on Continual Learning Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this dataset
Quality-scored:… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/continual-learning-papers.