Instructions to use apwic/nerui-base-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apwic/nerui-base-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="apwic/nerui-base-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("apwic/nerui-base-2") model = AutoModelForTokenClassification.from_pretrained("apwic/nerui-base-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from apwic/nerui-base-2: direct link, hf CLI and curl.
- Browser
- Download file 884 Bytes
-
https://huggingface.co/apwic/nerui-base-2/resolve/main/predict_results.json
- Command line
-
hf download hf://apwic/nerui-base-2/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/apwic/nerui-base-2/resolve/main/predict_results.json
884 Bytes
| { | |
| "predict_LOCATION_f1": 0.9959183673469387, | |
| "predict_LOCATION_number": 245, | |
| "predict_LOCATION_precision": 0.9959183673469387, | |
| "predict_LOCATION_recall": 0.9959183673469387, | |
| "predict_ORGANIZATION_f1": 0.9912826899128271, | |
| "predict_ORGANIZATION_number": 401, | |
| "predict_ORGANIZATION_precision": 0.9900497512437811, | |
| "predict_ORGANIZATION_recall": 0.9925187032418953, | |
| "predict_PERSON_f1": 1.0, | |
| "predict_PERSON_number": 396, | |
| "predict_PERSON_precision": 1.0, | |
| "predict_PERSON_recall": 1.0, | |
| "predict_loss": 0.00908414926379919, | |
| "predict_overall_accuracy": 0.9989210185584808, | |
| "predict_overall_f1": 0.9956834532374101, | |
| "predict_overall_precision": 0.9952061361457335, | |
| "predict_overall_recall": 0.9961612284069098, | |
| "predict_runtime": 0.7176, | |
| "predict_samples_per_second": 592.233, | |
| "predict_steps_per_second": 9.754 | |
| } |