Instructions to use Conrad747/luganda-ner-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Conrad747/luganda-ner-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Conrad747/luganda-ner-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Conrad747/luganda-ner-v3") model = AutoModelForTokenClassification.from_pretrained("Conrad747/luganda-ner-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58fa52358edd82145b20dc21508bb908cb901ef628e9e46cc819568630875c38
- Size of remote file:
- 3.58 kB
- SHA256:
- 28d0b30de381fe49612ab7fec238775a528bf607b634df61ed837291259baad7
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