Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
species-recognition
taxonomy
organism-identification
biology
species
Instructions to use OpenMed/OpenMed-NER-SpeciesDetect-BioMed-109M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-SpeciesDetect-BioMed-109M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-SpeciesDetect-BioMed-109M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-SpeciesDetect-BioMed-109M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-SpeciesDetect-BioMed-109M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27375d82bf2e8025c4f997018d38bbda1477ae4ae56cc3b195f2bf20810a960a
- Size of remote file:
- 218 MB
- SHA256:
- 8a01c9705f9ee9d4af6abf4edab6f72d102a40297e69182af4940beff20f2fb7
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