Token Classification
Transformers
Safetensors
mt5
named-entity-recognition
hausa
african-language
pii-detection
Generated from Trainer
Eval Results (legacy)
Instructions to use Beijuka/mt5-base-hausa-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Beijuka/mt5-base-hausa-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Beijuka/mt5-base-hausa-ner-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Beijuka/mt5-base-hausa-ner-v1") model = AutoModelForTokenClassification.from_pretrained("Beijuka/mt5-base-hausa-ner-v1") - Notebooks
- Google Colab
- Kaggle
Ctrl+K