Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
protein-recognition
gene-recognition
molecular-biology
genomics
dna
rna
cell_line
cell_type
protein
Instructions to use OpenMed/OpenMed-NER-DNADetect-BioPatient-108M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DNADetect-BioPatient-108M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DNADetect-BioPatient-108M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DNADetect-BioPatient-108M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DNADetect-BioPatient-108M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13ca9f51b59ec111799a2c3ec25346af0d00b9dc32230151d40cc9b8e5b3c430
- Size of remote file:
- 215 MB
- SHA256:
- 917a12ae09ba5e4f5e5f09f194a4e241911493977559e148d48f252911311c62
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