Instructions to use violetar/Ner-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use violetar/Ner-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="violetar/Ner-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("violetar/Ner-model") model = AutoModelForTokenClassification.from_pretrained("violetar/Ner-model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "test_accuracy": 0.9749472650041899, | |
| "test_f1": 0.8915077989601387, | |
| "test_loss": 0.30494070053100586, | |
| "test_precision": 0.8730482009504412, | |
| "test_recall": 0.9107648725212465, | |
| "test_runtime": 201.6979, | |
| "test_samples_per_second": 17.12, | |
| "test_steps_per_second": 1.071 | |
| } |