compact
BTL-4-CompactMinerU-HTML-v1.1-hunyuan0.5B-compactQwen3.5-27B-Gemini3-Pro-High-Reasoning-Compact-Thinking-i1-GGUFqwen3.5-35b-a3b-compacted-GGUFqwen3-coder-30b-a3b-compacted-19b-256kCompactor-Qwen3.5-4B-GGUFQwen3.5-122B-A10B-Uncensored-APEX-Compact-GGUFTheDrummer_Orion-26B-A4B-v1-GGUF-I-Compact-MXFP4-GGUF
Datasets
All datasets matching “compact”compact-alignments
compact-alignments — per-verse, per-book, content-addressed
The token-position companion to lexeme-alignments (which is
aggregated/type-level and can't tell you what happened in any one verse). This dataset restores
position: for a given edition's Bible book, which Hebrew/Greek content word aligned to which
target-text token, verse by verse.
The authoritative list of what's published is always manifest.json, not this file.
Original-language source editions (needed… See the full description on the dataset page: https://huggingface.co/datasets/bcv-commons/compact-alignments.CompactDS-102GB
Introduction
CompactDS is a diverse, high-quality, web-scale datastore that achieves high retrieval accuracy and subsecond latency on a single-node deployment, making it suitable for academic use. Its core design combines a compact set of high-quality, diverse data sources with in-memory approximate nearest neighbor (ANN) retrieval and on-disk exact search. We release CompactDS and our retrieval pipeline as a fully reproducible alternative to commercial search, supporting future… See the full description on the dataset page: https://huggingface.co/datasets/alrope/CompactDS-102GB.Compact_OpenAIRE_citation_graph
📚 Compact OpenAIRE Citation Graph
Based on OpenAIRE Graph v11.1.1 (source on Zenodo).
The complete OpenAIRE citation graph, distilled into a handful of compact, analysis-ready files — the full scholarly citation network of the open-science ecosystem, small enough to actually work with.
Citation graphs at this scale are usually locked behind multi-terabyte dumps and heavyweight infrastructure. This dataset makes the entire OpenAIRE citation network loadable… See the full description on the dataset page: https://huggingface.co/datasets/Zmeos/Compact_OpenAIRE_citation_graph.FlexiSLM-Data-2M-s2s-compact
FlexiSLM-Data — Speech-to-Speech Part (2.43M filtered samples, 385G in size)
Paper: https://arxiv.org/abs/2606.31247
Demo page: https://flexislm.github.io/
Code: https://github.com/AmphionTeam/FlexiSLM
FlexiSLM-Data is a large-scale, single-turn English speech-to-speech dialogue dataset
for training FlexiSLM, a spoken language model.
This repository contains the paired prompt-and-response audio portion of the release in
WebDataset format.
Related data releases… See the full description on the dataset page: https://huggingface.co/datasets/FlexiSLM/FlexiSLM-Data-2M-s2s-compact.slm-parameter-audit
SLM card-vs-artifact parameter audit
An autonomous audit of small-language-model repos on the Hugging Face Hub. For each
in-scope model (independent builders training very small models from scratch, roughly
0.5M–500M parameters), the parameter count stated in the model card is compared against
the actual artifact: the safetensors header, config.json, and the training script where
present. A mismatch is recorded when the card's number does not match the artifact's
real parameter… See the full description on the dataset page: https://huggingface.co/datasets/Compactbot/slm-parameter-audit.Gargantua-R1-Compact
Gargantua-R1 Distribution
Gargantua-R1-Compact(experimental purpose)
Gargantua-R1-Compact is a large-scale, high-quality reasoning dataset primarily designed for mathematical reasoning and STEM education. It contains approximately 6.67 million problems and solution traces, with a strong emphasis on mathematics (over 70%), as well as coverage of scientific domains, algorithmic challenges, and creative logic puzzles. The dataset is suitable for training and evaluating… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Compact.