Instructions to use chintagunta85/electramed-small-ADE-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/electramed-small-ADE-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/electramed-small-ADE-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/electramed-small-ADE-ner") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/electramed-small-ADE-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66458ea098d9df7c570cb5455452c870cdec551a43668d47340dbc18a8164db6
- Size of remote file:
- 54 MB
- SHA256:
- dd6983d31d6f9c78908d6d4d3e62d36ceabeb5fe922a8b74c62e88518fe64994
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