datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bitcoin-wallet-recovery-faq
Bitcoin Wallet Recovery FAQ Dataset v1.0
A high-quality Question & Answer dataset focused exclusively on Bitcoin wallet recovery and self-custody best practices. It is designed for training, fine-tuning, and evaluating LLMs and retrieval-augmented generation (RAG) systems in the domain of bitcoin security, seed backup, device loss, and fund recovery.
Dataset Summary
Total records: 500
Language: English
Answer length: 150–300 words per record
Categories: 39… See the full description on the dataset page: https://huggingface.co/datasets/ismailtasdelen/bitcoin-wallet-recovery-faq.bitcoin-security-reasoning-100k
Dataset Card for Bitcoin Security Reasoning 100K
100,000 high-quality synthetic training samples for fine-tuning LLMs on Bitcoin protocol security analysis. Teaches models to analyze vulnerability clusters, form security hypotheses, and generate differential testing code.
Dataset Details
Dataset Description
This dataset contains structured security reasoning chains for Bitcoin protocol vulnerabilities. Each sample presents a cluster of causal… See the full description on the dataset page: https://huggingface.co/datasets/davidfoss/bitcoin-security-reasoning-100k.bitcoin-price-explosion-qa
Bitcoin Price Explosion QA
A long-form, multi-hop question answering dataset about Bitcoin's historic surge past $100,000 following the 2024 US presidential election.
Dataset Description
This dataset contains 20 expert-curated causal reasoning questions grounded in 20 news articles covering Bitcoin's price explosion in late 2024. Each question requires synthesizing information from multiple source documents to produce a comprehensive answer, making it a challenging… See the full description on the dataset page: https://huggingface.co/datasets/jashparekh/bitcoin-price-explosion-qa.KIMI-K2.5-1000000x
KIMI-K2.5-1000000x
1,000,000 reasoning traces distilled from KIMI-K2.5 on high reasoning, (Each subset has different questions)
Distribution:
Coding: 50% (Includes: Webdev, Python, C++, Java, JS, C, Ruby, Lua, Rust, and C#)
Science: 20% (Physics, Chemistry, Biology) - 100k more completions in the PHD-Science subset
Math: 15% (Algebra, Calculus, Probability) - 200k more completions in kimiMath200k.jsonl
Computer Science: 5%
Logical Questions: 5%
Creative Writing: 5%… See the full description on the dataset page: https://huggingface.co/datasets/bitsydarel/KIMI-K2.5-1000000x.