Token Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use peteryushunli/bert-finetuned-hausa_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peteryushunli/bert-finetuned-hausa_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="peteryushunli/bert-finetuned-hausa_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("peteryushunli/bert-finetuned-hausa_ner") model = AutoModelForTokenClassification.from_pretrained("peteryushunli/bert-finetuned-hausa_ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9196e79909b9e182f2c9677e136ca9c017396121bd06e9fe34d3d82757b2bc37
- Size of remote file:
- 431 MB
- SHA256:
- 09737665023d1da0d485776c1ae90c192f0c06629b93b70ab292c391c8262a05
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.