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: 346 Bytes
537853b | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"epoch": 5.0,
"eval_accuracy": 0.9984689190568541,
"eval_f1": 0.7999999999999999,
"eval_loss": 0.014412553049623966,
"eval_precision": 0.7407407407407407,
"eval_recall": 0.8695652173913043,
"eval_runtime": 3.1077,
"eval_samples": 505,
"eval_samples_per_second": 162.502,
"eval_steps_per_second": 40.867
} |