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:
- 3bbf51665e76b45a459a7702710e6cdaa387518989b1cdf4ad103701bf8c6d00
- Size of remote file:
- 16.3 MB
- SHA256:
- bbef9712c55ef75d0004007743c550a957b55a8f094bec9f147c42dc093ab471
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