# Multi-label Recognition

GLiNER-BioMed is an efficient open biomedical named entity recognition model suite based on the GLiNER framework, specifically designed for the biomedical domain, capable of recognizing multiple entity types.

A lightweight zero-shot object detection model in ONNX format, compatible with Transformers.js, suitable for browser-side deployment.

A classification model fine-tuned based on the bert-base-uncased model, achieving 91.13% accuracy on specific tasks

A multi-label image classification model fine-tuned based on Google Vision Transformer, specifically designed to identify content in screenshots from the animated series 'Futurama'.