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
File size: 332 Bytes
904bd0a | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"epoch": 10.0,
"eval_accuracy": 0.985104873847401,
"eval_f1": 0.911088911088911,
"eval_loss": 0.09563781321048737,
"eval_precision": 0.890625,
"eval_recall": 0.9325153374233128,
"eval_runtime": 1.2647,
"eval_samples": 161,
"eval_samples_per_second": 127.3,
"eval_steps_per_second": 32.418
} |