Instructions to use Conrad747/luganda-ner-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Conrad747/luganda-ner-v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Conrad747/luganda-ner-v4")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Conrad747/luganda-ner-v4") model = AutoModelForTokenClassification.from_pretrained("Conrad747/luganda-ner-v4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c4197c2e24baf950931f299503080ea3b99843f432b50f342ec3525efdd98df
- Size of remote file:
- 735 MB
- SHA256:
- 41b2352d757e2d97e0818034523550970af74a1aef500ffed7d40e0339f99e00
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