Token Classification
Transformers
TensorBoard
Safetensors
English
deberta-v2
named-entity-recognition
sequence-tagger-model
Instructions to use Babelscape/cner-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babelscape/cner-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Babelscape/cner-base")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Babelscape/cner-base") model = AutoModelForTokenClassification.from_pretrained("Babelscape/cner-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Babelscape/cner-base: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/Babelscape/cner-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://Babelscape/cner-base/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Babelscape/cner-base/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.