Instructions to use apwic/nerui-base-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/nerui-base-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="apwic/nerui-base-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("apwic/nerui-base-1") model = AutoModelForTokenClassification.from_pretrained("apwic/nerui-base-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from apwic/nerui-base-1: direct link, hf CLI and curl.
- Browser
- Download file 883 Bytes
-
https://huggingface.co/apwic/nerui-base-1/resolve/main/predict_results.json
- Command line
-
hf download hf://apwic/nerui-base-1/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/apwic/nerui-base-1/resolve/main/predict_results.json
883 Bytes
| { | |
| "predict_LOCATION_f1": 0.9915966386554622, | |
| "predict_LOCATION_number": 237, | |
| "predict_LOCATION_precision": 0.9874476987447699, | |
| "predict_LOCATION_recall": 0.9957805907172996, | |
| "predict_ORGANIZATION_f1": 0.986013986013986, | |
| "predict_ORGANIZATION_number": 431, | |
| "predict_ORGANIZATION_precision": 0.990632318501171, | |
| "predict_ORGANIZATION_recall": 0.9814385150812065, | |
| "predict_PERSON_f1": 1.0, | |
| "predict_PERSON_number": 371, | |
| "predict_PERSON_precision": 1.0, | |
| "predict_PERSON_recall": 1.0, | |
| "predict_loss": 0.011574001982808113, | |
| "predict_overall_accuracy": 0.9987315010570824, | |
| "predict_overall_f1": 0.9922928709055877, | |
| "predict_overall_precision": 0.9932497589199615, | |
| "predict_overall_recall": 0.9913378248315688, | |
| "predict_runtime": 0.7844, | |
| "predict_samples_per_second": 541.828, | |
| "predict_steps_per_second": 8.924 | |
| } |