{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/3"}],"enrichment":{"capability":"Integrates curated transformer models (ALBERT, BERT, CamemBERT, RoBERTa, XLM-RoBERTa) into spaCy pipelines via the curated-transformers library.","skillfed_tags":["nlp","transformers","spacy-extension"],"use_cases":["Build spaCy NLP pipelines powered by BERT or RoBERTa for named entity recognition","Deploy transformer-based models in production with spaCy's serialization and config system","Train multi-task learning models combining transformers with spaCy components","Use XLM-RoBERTa for multilingual NLP tasks within a spaCy pipeline","Experiment with model distillation and quantization for deployment optimization"],"what_it_does":"spacy-curated-transformers is a spaCy extension that wraps the curated-transformers library to bring transformer-based NLP models into spaCy pipelines. It provides integration with spaCy's architecture system, allowing you to use pretrained models like BERT, RoBERTa, and XLM-RoBERTa as components in your NLP workflows. The package emphasizes minimal dependencies and deployment-focused features such as model distillation and quantization.\n\nYou use it by installing it alongside spaCy, then configuring transformer models in your spaCy pipeline config to power tasks like named entity recognition or text classification. It supports multi-task learning and integrates with Hugging Face Hub for model discovery. The package is maintained by Explosion AI and handles the integration between spaCy and the curated-transformers library, managing serialization, configuration, and execution of transformer models in production pipelines.","worth_installing":"Yes, if you need transformer models in spaCy pipelines and want a maintained integration. The package is actively developed, has low install friction, and is MIT-licensed. It requires Python >=3.9 and substantial dependencies (torch, curated-transformers), so confirm those fit your environment. No known security vulnerabilities."},"id":"spacy-curated-transformers","links":{"html":"https://skillfed.io/packages/spacy-curated-transformers","md":"https://skillfed.io/packages/spacy-curated-transformers.md","pypi":"https://pypi.org/project/spacy-curated-transformers/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2024-09-30","license_spdx":null,"license_treatment":"permissive","name":"spacy-curated-transformers","python_support":"supports_current","summary":"Curated transformer models for spaCy pipelines"},"popularity":{"monthly_downloads":1487380,"position":3846,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2.1.2"}