Instructions to use dronenlp/DroNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dronenlp/DroNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dronenlp/DroNER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dronenlp/DroNER") model = AutoModelForTokenClassification.from_pretrained("dronenlp/DroNER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5ffd53add7ad254cfa03d1d2ea550977e4fcce97e6c7365567561d68e8a2b20
- Size of remote file:
- 3.13 kB
- SHA256:
- baf430a9b1158b1cf056e37ad4ed459a10ef4207aad754f2310de36625c460f9
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