Token Classification
Transformers
Safetensors
English
roberta
named-entity-recognition
biomedical-nlp
species-recognition
taxonomy
organism-identification
biodiversity
species
Instructions to use OpenMed/OpenMed-NER-OrganismDetect-TinyMed-82M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-OrganismDetect-TinyMed-82M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-OrganismDetect-TinyMed-82M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-TinyMed-82M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-TinyMed-82M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ced26700151f165af833086f2931a879c8d36eda9d7bd23ee12d7377b313b5d9
- Size of remote file:
- 163 MB
- SHA256:
- c954acb322f85e73aa83bf78c59cf87fd0307834522371f5b4aa34b943f221cd
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