Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
species-recognition
taxonomy
organism-identification
biodiversity
species
Instructions to use OpenMed/OpenMed-NER-OrganismDetect-PubMed-109M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-OrganismDetect-PubMed-109M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-OrganismDetect-PubMed-109M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-PubMed-109M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-PubMed-109M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43dd48a6e25b015fbf237ceb7846507c1ac108ca84d45f34f6fb074764ab89e9
- Size of remote file:
- 218 MB
- SHA256:
- 0693118529572adb58e620936265e78039572afabeb38a1dae253e2614f372fd
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