GitHub Typo Corpus: Largest Dataset of Misspellings and Grammar Errors
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical Errors - mhagiwara/github-typo-corpus
GitHub Typo Corpus: Largest Dataset of Misspellings and Grammar Errors launched on December 2, 2019 with 8 votes, #864 of 2,946 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 6 years on.
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Fine-grained stylistic control of LLMs using model arithmetic2023 · github.com · ▲85We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
We fingerprinted 178 AI models' writing styles and similarity clustersApr 2026 · rival.tips · ▲78We have a dataset of 3,095 standardized AI responses across 43 prompts. From each response, we extract a 32-dimension stylometric fingerprint (lexical richness, sentence structure, punctuation habits, formatting patterns, discourse markers). Some findings: - 9 clone clusters (>90% cosine similarity on z-normalized feature vectors) - Mistral Large 2 and Large 3 2512 score 84.8% on a composite metric combining 5 independent signals - Gemini 2.5 Flash Lite writes 78% like Claude 3 Opus. Costs 185x less - Meta has the strongest provider "house style" (37.5x distinctiveness ratio) - "Satirical…
- ITI trained a GPT-2 1.5B Subreddit Simulator in 3 days using 88 TPUs2019 · pastebin.com · ▲10
Pastebin.com is the number one paste tool since 2002. Pastebin is a website where you can store text online for a set period of time.
SemHash – Fast Semantic Text Deduplication for Cleaner Datasets2025 · github.com · ▲19We’ve just open-sourced SemHash, a lightweight package for semantic text deduplication. It lets you effortlessly clean up your datasets and avoid pitfalls caused by duplicate samples in semantic search, RAG, and machine learning. Main Features: - Fast and hardware friendly: Deduplicate datasets with millions of records in minutes, on a CPU. - Flexible: Works on single or multiple datasets (e.g., train/test deduplication), and multi-column data (e.g., Question-Answering datasets). - Lightweight: Minimal dependencies (largest is NumPy). - Explainable: Easily inspect duplicates and what…
Improve Text-to-SQL Accuracy with LLM2023 · github.com · ▲17A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub
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