Instructions to use Wanjiru/bert-base-multilingual_en_ner_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wanjiru/bert-base-multilingual_en_ner_ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Wanjiru/bert-base-multilingual_en_ner_")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Wanjiru/bert-base-multilingual_en_ner_") model = AutoModelForTokenClassification.from_pretrained("Wanjiru/bert-base-multilingual_en_ner_") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Wanjiru/bert-base-multilingual_en_ner_")
model = AutoModelForTokenClassification.from_pretrained("Wanjiru/bert-base-multilingual_en_ner_")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Label ID Label Name 0 0
B-PERI-PERB-ORGI-ORGB-LOCI-LOC
- Downloads last month
- 5
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Wanjiru/bert-base-multilingual_en_ner_")