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-PubMed-335M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-DNADetect-PubMed-335M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-DNADetect-PubMed-335M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-DNADetect-PubMed-335M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-DNADetect-PubMed-335M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebc7a53e98f4ac2453e38542831d88ae28c359b134626c005b56cac66d178146
- Size of remote file:
- 668 MB
- SHA256:
- b003b0b1af219c621cd2e38ba3cc9a422d427575d9da3017c20da9525febd891
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