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Multi-label Recognition

# Multi-label Recognition

Gliner Biomed Bi Base V1.0
Apache-2.0
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.
Sequence Labeling English
G
Ihor
25
1
Grounding Dino Tiny ONNX
Apache-2.0
A lightweight zero-shot object detection model in ONNX format, compatible with Transformers.js, suitable for browser-side deployment.
Object Detection Transformers
G
onnx-community
98
1
Bert Base Uncased Finetuned Sdg Mar23
Apache-2.0
A classification model fine-tuned based on the bert-base-uncased model, achieving 91.13% accuracy on specific tasks
Text Classification Transformers
B
jonas
357
3
Vit Base Patch16 224 Futurama Image Multilabel Clf
Apache-2.0
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'.
Image Classification Transformers English
V
DunnBC22
19
1
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