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:
- d28326e6516eb31a17e82fe66ed8de283410bba162d45b5c83719197adf07c8a
- Size of remote file:
- 1.11 GB
- SHA256:
- d5cc9b7eb748d73b8e5d1d1aa9ade4051451efbd33c0d050d45af8b8bd2553f8
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