Token Classification
Transformers
Safetensors
English
roberta
named-entity-recognition
biomedical-nlp
anatomical-entity-recognition
medical-terminology
anatomy
healthcare
Instructions to use OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-SuperMedical-125M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
cf0b5ee | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:749ceac1ff123c631f82df2a9cc39abcacd34783eb7ebb573cd606bfb6652b3c
size 248138750
|