Category
Explore by categories
A human-verified subset of 500 SWE-bench test cases for evaluating models that resolve GitHub issues into PRs using unit-test verification. Contains problem statements and base commits (pre-fix) for reproducible unit-test based evaluation; suitable for benchmarking code-fix and issue-resolution capabilities.
Physics-aware simulated sensor dataset for training and evaluating autonomous-vehicle perception and control models. Includes multimodal sensor streams with physical-scene annotations intended for tasks that require grounding in real-world dynamics.
1,000,000 US-focused synthetic persona records (6M persona texts) grounded to demographic, geographic and personality distributions. Contains age, sex, education, occupation and ZCTA/city fields; CC BY 4.0 license for LLM training, diversity augmentation, and bias mitigation.
A collection of ready-to-run Hugging Face Jobs OCR scripts that add a markdown column (or structured JSON) to image datasets, with model switching, layout detection, server-mode serving, and per-model options for table/form extraction.
A ~3.2M-conversation Hugging Face dataset of non-toxic human–ChatGPT interactions for instruction finetuning and evaluation; includes full transcripts plus request headers, hashed IP/geolocation, turn-level moderation scores and usage metadata.
A large multi-config collection of query–document pairs assembled to reproduce and extend the mGTE/LateOn data recipe for pre-training text embedding models. Data come in source-specific configs and include per-row drop/duplicate flags and guidance for using cleaned subsets for training.
Benchmark dataset for evaluating agents on long-horizon software-engineering tasks (repo-level patches, test-driven fixes). Includes golden patches, related tests, and problem statements in parquet format; aimed at agent debugging and code-modification evaluation but requires full test environments.
A 1,000,000-sample Vietnamese historical conversation dataset in ShareGPT/ChatML format for question-answering and text-generation. Approximately 78% of samples include step-by-step reasoning chains; remaining samples are final-only. Useful for training or evaluating Vietnamese LLMs and chat agents.
Provides a 10,000-hour Sichuanese (Chuan-Yu) speech corpus with rich annotations (timestamps, speaker age/gender/emotion, SNR, DNSMOS) and unified metadata for ASR and TTS research; includes metadata.jsonl, evaluation benchmarks, and an LLM-assisted transcription pipeline.
Provides 99,870 system/user/assistant chat triples for defensive cybersecurity instruction‑tuning, with built‑in refusal patterns and mapping to OWASP, MITRE ATT&CK, NIST, and CIS standards; Apache‑2.0 licensed.
Provides mined hard negatives and relevance scores for 1.88M queries across seven retrieval datasets, enabling contrastive fine-tuning and nv-retrieve filtering; includes full 2048 mined negatives per query, paired query/document splits, and parquet-formatted files for large-scale training.
Aggregates SEC EDGAR filings into raw files, parsed plaintext, and rich filing metadata for LLM training and retrieval. Includes ~8.05M filings (~590 GB, ~43B tokens), per-filing token counts, and parsed outputs; Apache-2.0.