Token Classification
Transformers
Safetensors
xlm-roberta
code-switching
yoruba
african-nlp
language-identification
lid
Eval Results (legacy)
Instructions to use Professor/yoruba-en-ner-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Professor/yoruba-en-ner-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Professor/yoruba-en-ner-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Professor/yoruba-en-ner-model") model = AutoModelForTokenClassification.from_pretrained("Professor/yoruba-en-ner-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa1e2650dc460ce2fc52426f3b1d8873bcb0148a306f4c79dbdf2c5f40db5362
- Size of remote file:
- 5.84 kB
- SHA256:
- 6b9f172da5635eecd909548784194e4045eb9f7322fbf8ad67661f698b6617b0
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