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-PubMed-v2-109M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-SpeciesDetect-PubMed-v2-109M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-SpeciesDetect-PubMed-v2-109M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-SpeciesDetect-PubMed-v2-109M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-SpeciesDetect-PubMed-v2-109M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1659487fe31e260f306a07112d122a28eabbe7d53edf0f474aa03d2704e4fb44
- Size of remote file:
- 218 MB
- SHA256:
- 6d307b59859628a91acd06424b55b19b84db9a94ddbb81ff0b6c4a2adce7152a
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