Instructions to use nhanv/ner_cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/ner_cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nhanv/ner_cv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nhanv/ner_cv") model = AutoModelForTokenClassification.from_pretrained("nhanv/ner_cv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e233c8112e3978148ce943a31b0a7caa571f739023f40e29818d58e625eec8b
- Size of remote file:
- 3.38 kB
- SHA256:
- 809dfcb1e2f8c5c4d1e1187ff6c6c59fb502aab130e01409079ca67d7c9e76af
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