Instructions to use apwic/nerui-base-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/nerui-base-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="apwic/nerui-base-4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("apwic/nerui-base-4") model = AutoModelForTokenClassification.from_pretrained("apwic/nerui-base-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from apwic/nerui-base-4: direct link, hf CLI and curl.
- Browser
- Download file 868 Bytes
-
https://huggingface.co/apwic/nerui-base-4/resolve/main/predict_results.json
- Command line
-
hf download hf://apwic/nerui-base-4/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/apwic/nerui-base-4/resolve/main/predict_results.json
868 Bytes
| { | |
| "predict_LOCATION_f1": 1.0, | |
| "predict_LOCATION_number": 256, | |
| "predict_LOCATION_precision": 1.0, | |
| "predict_LOCATION_recall": 1.0, | |
| "predict_ORGANIZATION_f1": 0.9986282578875172, | |
| "predict_ORGANIZATION_number": 365, | |
| "predict_ORGANIZATION_precision": 1.0, | |
| "predict_ORGANIZATION_recall": 0.9972602739726028, | |
| "predict_PERSON_f1": 0.9942028985507246, | |
| "predict_PERSON_number": 344, | |
| "predict_PERSON_precision": 0.9913294797687862, | |
| "predict_PERSON_recall": 0.997093023255814, | |
| "predict_loss": 0.005500253289937973, | |
| "predict_overall_accuracy": 0.9994526546250684, | |
| "predict_overall_f1": 0.9974106680476439, | |
| "predict_overall_precision": 0.9968944099378882, | |
| "predict_overall_recall": 0.9979274611398964, | |
| "predict_runtime": 0.7313, | |
| "predict_samples_per_second": 582.51, | |
| "predict_steps_per_second": 9.572 | |
| } |