#Inference API

SpanMarker provides a robust framework for Named Entity Recognition, using encoders such as BERT, RoBERTa, and ELECTRA. It integrates with the Hugging Face Transformers library, offering features like model management, hyperparameter tuning, and mixed precision training. SpanMarker enhances usability by supporting different annotation schemes and enables seamless access to the Hugging Face Hub, including a free API for fast deployment. It is suitable for developers aiming to train or utilize high-performance NER models on datasets like FewNERD and OntoNotes5.

This collection of JavaScript libraries is designed to facilitate direct interaction with the Hugging Face API. It includes TypeScript support and is compatible with modern platforms like Node.js, Bun, and Deno, eliminating the requirement for polyfills. The libraries enable efficient machine learning model management, including repository management, file upload, and Inference API use for tasks like chat completion and image-to-text conversion. These tools cater to developers aiming for effective integration with Hugging Face's extensive model hub, offering practical solutions for various machine learning applications.