Token Classification
Transformers
Safetensors
English
xlm-roberta
named-entity-recognition
biomedical-nlp
gene-recognition
protein-recognition
genomics
molecular-biology
gene/protein
Instructions to use OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-BigMed-278M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c6ea87e3e52bb3f864db4c88be6cd2c0d66d17042d8cf403fb3b0642cf431f1
- Size of remote file:
- 14.8 MB
- SHA256:
- da145b5e7700ae40f16691ec32a0b1fdc1ee3298db22a31ea55f57a966c4a65d
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