Instructions to use NeuronZero/MED-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuronZero/MED-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NeuronZero/MED-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("NeuronZero/MED-NER") model = AutoModelForTokenClassification.from_pretrained("NeuronZero/MED-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68f35c69c6b835b120ef9ed3edc9c0f4f741f81373f0d08935da5cfdaca0625c
- Size of remote file:
- 736 MB
- SHA256:
- 9fa0137fc2d0383aefa8cbb7dcce0e85ccc7f88290951419ac54a160343aaf7d
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