Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
gene-recognition
protein-recognition
genomics
molecular-biology
gene/protein
Instructions to use OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-GenomeDetect-PubMed-109M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8161c758cb57832014f726c17727e16561e52e21002c15d3b655ffdc3712d6e6
- Size of remote file:
- 218 MB
- SHA256:
- bf1a568aa49910dc2e457f80cc8abd9705151599c89d92348878115b52c71612
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