{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/6"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"}],"enrichment":{"capability":"fasttext-numpy2 provides Python bindings for fastText, a library for learning word representations and training text classifiers, with compatibility fixes for numpy 2.","skillfed_tags":["word-embeddings","text-classification","numpy2-compat"],"use_cases":["Train word embeddings on raw text corpora for downstream NLP tasks like similarity search or clustering.","Build and evaluate text classifiers on labeled datasets with built-in precision/recall metrics.","Compress trained supervised models using quantization to deploy smaller, faster inference artifacts.","Migrate existing fastText code to numpy 2 environments without rewriting bindings.","Extract word vectors for a given vocabulary to use as features in other machine learning pipelines."],"what_it_does":"fasttext-numpy2 is a fork of Facebook's fastText library that adds compatibility with numpy 2, addressing breaking changes in the original package. It provides Python bindings for training unsupervised word representation models (skipgram and CBOW) and supervised text classifiers. The package handles UTF-8 encoded text input, tokenizes it, and learns dense vector representations of words or classifies documents based on labeled training data.\n\nThe library depends on pybind11 for Python-C++ interop, setuptools for building, and numpy for numerical operations. It ships precompiled wheels for Python 3.6 through 3.13 on Linux x86_64, reducing installation friction for those platforms. Model objects can be saved, loaded, and quantized to reduce file size with minimal accuracy loss.","worth_installing":"Yes, if you need fastText with numpy 2 support and accept the dormant maintenance status. The package is stable (0.10.4 release), has no known vulnerabilities, and carries a permissive MIT license. However, the repository has not been updated in 644 days and is archived; consider whether you can tolerate lack of future bug fixes or feature updates. For active development or long-term production use, evaluate whether the original fastText package or an actively maintained alternative better fits your risk tolerance."},"id":"fasttext-numpy2","links":{"html":"https://skillfed.io/packages/fasttext-numpy2","md":"https://skillfed.io/packages/fasttext-numpy2.md","pypi":"https://pypi.org/project/fasttext-numpy2/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-11-08","license_spdx":null,"license_treatment":"permissive","name":"fasttext-numpy2","python_support":"unspecified","summary":"fasttext Python bindings, fixed numpy 2 compatibiliy"},"popularity":{"monthly_downloads":1046821,"position":4451,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.10.4"}