Hugging Face model: sassoftware/glitext-base-biomed
Author: sassoftware
Created: 2026-06-16 14:49:06
Last modified: 2026-06-19 16:46:55
Pipeline: token-classification
Library: glitext
Likes: 0 | Downloads: 0
Tags: glitext, pytorch, onnx, NER, GLiNER, information extraction, encoder, entity recognition, biomed, token-classification, en, dataset:anthonyyazdaniml/gliner-biomed-pre-training, dataset:anthonyyazdaniml/gliner-biomed-post-training, arxiv:2504.00676, arxiv:2311.08526, arxiv:2406.12925, base_model:microsoft/deberta-v3-base, base_model:quantized:microsoft/deberta-v3-base, license:apache-2.0, region:us
Base model relation: quantized
Base models: id: microsoft/deberta-v3-base
Card metadata:
base_model: microsoft/deberta-v3-base
datasets: anthonyyazdaniml/gliner-biomed-pre-training, anthonyyazdaniml/gliner-biomed-post-training
language: en
library_name: glitext
license: apache-2.0
metrics: f1
pipeline_tag: token-classification
tags: NER, GLiNER, information extraction, encoder, entity recognition, biomed, glitext
glitext: name: base-biomed
label: GliText Biomedical Recognition (Balanced)
description: An efficient zero-shot named entity recognition model tuned for biomedical text extraction with balanced speed and accuracy.
recognition: yes
classification: no
association: no
span_mode: yes
size_gb: 0.73
hf_repo: sassoftware/glitext-base-biomed
source_url: Ihor/gliner-biomed-base-v1.0