Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
Eval Results (legacy)
Instructions to use universalner/uner_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_all")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_all") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_all") - Notebooks
- Google Colab
- Kaggle
| { | |
| "predict_accuracy": 0.9861662964870078, | |
| "predict_f1": 0.8785117691723614, | |
| "predict_loss": 0.10341698676347733, | |
| "predict_precision": 0.883206106870229, | |
| "predict_recall": 0.8738670694864048, | |
| "predict_runtime": 45.4563, | |
| "predict_samples_per_second": 170.097, | |
| "predict_steps_per_second": 42.524 | |
| } |