Instructions to use Davlan/bert-base-multilingual-cased-ner-hrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/bert-base-multilingual-cased-ner-hrl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Davlan/bert-base-multilingual-cased-ner-hrl")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl") model = AutoModelForTokenClassification.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Add tokenizer.json
#9
by bu6n - opened
Generated with:
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("Davlan/bert-base-multilingual-cased-ner-hrl")
assert tokenizer.is_fast
tokenizer.save_pretrained("...")