Token Classification
Transformers
Safetensors
English
xlm-roberta
named-entity-recognition
biomedical-nlp
gene-recognition
genetics
genomics
molecular-biology
cell-line-name
Instructions to use OpenMed/OpenMed-NER-GenomicDetect-SnowMed-568M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-GenomicDetect-SnowMed-568M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-GenomicDetect-SnowMed-568M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-GenomicDetect-SnowMed-568M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-GenomicDetect-SnowMed-568M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a6f5c1e50e73c48966c481e6a614246f1f5e2e30bc3ac5b46b9858c1e2a6225
- Size of remote file:
- 1.13 GB
- SHA256:
- 6dbb6f9b3d0b103f6b4e5b8d167f2b8e00642fca1e58ea5f1c026339dbd00b17
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