Token Classification
Transformers
Safetensors
English
eurobert
named-entity-recognition
biomedical-nlp
gene-recognition
genetics
genomics
molecular-biology
cell-line-name
custom_code
Instructions to use OpenMed/OpenMed-NER-GenomicDetect-EuroMed-212M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-GenomicDetect-EuroMed-212M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-GenomicDetect-EuroMed-212M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-GenomicDetect-EuroMed-212M", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-GenomicDetect-EuroMed-212M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a06f099f2ba363a79de565fc6a2f43c234d7a01497063de84ce820686185458b
- Size of remote file:
- 424 MB
- SHA256:
- 52ed52b8609f64c25c497bed60920c9328ff7599c90db1023ab28095b515142a
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