{"data":{"slug":"plasticityai-magnitude","name":"magnitude","tagline":"A fast, efficient universal vector embedding utility package.","github_url":"https://github.com/plasticityai/magnitude","owner":"plasticityai","repo":"magnitude","owner_avatar_url":"https://avatars.githubusercontent.com/u/36324344?v=4","primary_language":"Python","stars":1668,"forks":122,"topics":["embeddings","fast","fasttext","gensim","glove","machine-learning","machine-learning-library","memory-efficient","natural-language-processing","nlp","python","vectors","word-embeddings","word2vec"],"archived":false,"github_pushed_at":"2023-08-03T00:59:57+00:00","maintenance_label":"Dormant","stars_delta_30d":2,"url":"https://www.graphcanon.com/tools/plasticityai-magnitude","markdown_url":"https://www.graphcanon.com/tools/plasticityai-magnitude.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/plasticityai-magnitude","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=plasticityai-magnitude","description":"A fast, efficient universal vector embedding utility package.","homepage_url":null,"license":"MIT","open_issues":41,"watchers":34,"ai_summary":"Magnitude is a Python library focused on providing fast and memory-efficient operations for vector embeddings, including integration with popular methods like FastText, Gensim, GloVe, and Word2Vec. It aims to streamline natural language processing tasks by offering optimized handling of word embeddings.","readme_excerpt":"## Installation\nYou can install this package with `pip`:\n```python\npip install pymagnitude # Python 2.7\npip3 install pymagnitude # Python 3\n```\n\nGoogle Colaboratory has some dependency issues with installing Magnitude due to conflicting dependencies. You can use the following snippet to install Magnitude on Google Colaboratory:\n```bash\n\n---\n\n# Install Magnitude on Google Colab\n! echo \"Installing Magnitude.... (please wait, can take a while)\"\n! (curl https://raw.githubusercontent.com/plasticityai/magnitude/master/install-colab.sh | /bin/bash 1>/dev/null 2>/dev/null)\n! echo \"Done installing Magnitude.\"\n```\n\n---\n\n## LICENSE and Attribution\n\nThis repository is licensed under the license found [here](LICENSE.txt).\n\n“[Seismic](https://thenounproject.com/ziman.jan/collection/weather/?i=1518266)” icon by JohnnyZi from the [Noun Project](https://thenounproject.com).","github_created_at":"2018-02-24T07:28:16+00:00","created_at":"2026-07-11T11:30:24.783727+00:00","updated_at":"2026-08-22T12:01:04.311666+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"embeddings","name":"embeddings"},{"slug":"fasttext","name":"fasttext"},{"slug":"gensim","name":"gensim"},{"slug":"glove","name":"glove"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"memory-efficient","name":"memory-efficient"},{"slug":"nlp","name":"nlp"},{"slug":"word-embeddings","name":"word-embeddings"}],"trust":{"provenance":{"is_fork":false,"github_id":122715432,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-22T12:01:03.568Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1115,"last_release_at":"2020-05-25T11:26:09Z","stars_delta_30d":2,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:30:26.011Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-22T12:01:04.029Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-22T12:01:04.029Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-22T12:01:04.029Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- When you need to perform memory-efficient operations on vector embeddings, including those from FastText or Word2Vec.","- For projects where you require direct integration with libraries like Gensim, without the need for additional middleware."],"when_not_to_use":["- If your project involves non-Python ecosystems, as Magnitude is strictly a Python library and thus not compatible with other programming environments.","- When the primary focus of your work does not include handling large vector embeddings or specific operations that benefit from memory efficiency provided by Magnitude."],"source":"enrich:decision_facts","observed_at":"2026-07-11T17:50:43.245Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Magnitude is a Python library for handling vector embeddings efficiently and quickly. It integrates with several popular embedding methods."}]}}