Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
named-entity-recognition
sequence-tagger-model
Instructions to use Babelscape/wikineural-multilingual-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babelscape/wikineural-multilingual-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Babelscape/wikineural-multilingual-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Babelscape/wikineural-multilingual-ner") model = AutoModelForTokenClassification.from_pretrained("Babelscape/wikineural-multilingual-ner") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39eae7677fbf835c80a1c48a6ba23768e4017e9259d89afe8d71e319160026bb
- Size of remote file:
- 709 MB
- SHA256:
- 34b3e27fbcd0b54c45cc08ffc7b4e07a7a301480b65cd6430bbbd34daa00f6a3
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