Instructions to use Posos/ClinicalNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Posos/ClinicalNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Posos/ClinicalNER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Posos/ClinicalNER") model = AutoModelForTokenClassification.from_pretrained("Posos/ClinicalNER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a492cb76ad2e47d1012b5b833b8e31acd257499c7ed63bfe3df4392f3875a58b
- Size of remote file:
- 1.11 GB
- SHA256:
- fd180fa0a00a9c828c66ef4c2088cfa16080b792bb6f0a3b6e43c7c7ad2235b0
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