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:
- 4eca21f6279cda31c3fde70a1e21a27a36dafc0f779b8faf7480661256cc3093
- Size of remote file:
- 431 MB
- SHA256:
- fa2fbef864fd518ffabec64a6dcd43166184971956bc484d6fc4933640d7d0d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.