Token Classification
Transformers
Safetensors
English
roberta
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-SuperMedical-355M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DNADetect-SuperMedical-355M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DNADetect-SuperMedical-355M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DNADetect-SuperMedical-355M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DNADetect-SuperMedical-355M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4b62bf36ea58aad742c547981db7790ab469b8e72664551c8e0fc756e8ff0a6
- Size of remote file:
- 709 MB
- SHA256:
- aa4914e933f035a0060714018476166b227e9209672ee25c505d211b8c421911
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