Instructions to use universalner/uner_swe_tal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use universalner/uner_swe_tal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="universalner/uner_swe_tal")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("universalner/uner_swe_tal") model = AutoModelForTokenClassification.from_pretrained("universalner/uner_swe_tal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 325 Bytes
537853b | 1 2 3 4 5 6 7 8 9 10 | {
"predict_accuracy": 0.9977425528782451,
"predict_f1": 0.8826530612244898,
"predict_loss": 0.012470759451389313,
"predict_precision": 0.8826530612244898,
"predict_recall": 0.8826530612244898,
"predict_runtime": 7.337,
"predict_samples_per_second": 166.281,
"predict_steps_per_second": 41.57
} |