Instructions to use nhanv/cv_parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/cv_parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nhanv/cv_parser")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nhanv/cv_parser") model = AutoModelForTokenClassification.from_pretrained("nhanv/cv_parser") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b31f14afae1b4779d1a1958987f8a1393456c4ec4c42479a07ea01d9ff0fa982
- Size of remote file:
- 3.38 kB
- SHA256:
- 872b0c9a30857c46bfc90e2d51e67a262aea692254c5bde161bebb6cafe01c96
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