Token Classification
spaCy
Transformers
English
clinical-nlp
medication-ner
med7
Eval Results (legacy)
Instructions to use kormilitzin/en_core_med7_trf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use kormilitzin/en_core_med7_trf with spaCy:
!pip install https://huggingface.co/kormilitzin/en_core_med7_trf/resolve/main/en_core_med7_trf-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_core_med7_trf") # Importing as module. import en_core_med7_trf nlp = en_core_med7_trf.load() - Transformers
How to use kormilitzin/en_core_med7_trf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kormilitzin/en_core_med7_trf")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kormilitzin/en_core_med7_trf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K