Instructions to use GebeyaTalent/NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GebeyaTalent/NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="GebeyaTalent/NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("GebeyaTalent/NER") model = AutoModelForTokenClassification.from_pretrained("GebeyaTalent/NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14e89f361c8fc81b42b8ac7d2ee644076361fb7c14a3f803047d3e37197b133a
- Size of remote file:
- 436 MB
- SHA256:
- 70c32bd074ce9b7db5f8e8072e8019cb1389e2a4dc83a6ea3268b327995badf4
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