Instructions to use e4gl33y3/luganda-ner-v6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use e4gl33y3/luganda-ner-v6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="e4gl33y3/luganda-ner-v6")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("e4gl33y3/luganda-ner-v6") model = AutoModelForTokenClassification.from_pretrained("e4gl33y3/luganda-ner-v6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0abd02c8ae3c446b4b196b4041ef6b8dc3dce7d172091fa5ca5ce17b4eb7d627
- Size of remote file:
- 17.1 MB
- SHA256:
- f59925fcb90c92b894cb93e51bb9b4a6105c5c249fe54ce1c704420ac39b81af
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