Instructions to use THemidli/applied-ner-stage3-bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use THemidli/applied-ner-stage3-bert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="THemidli/applied-ner-stage3-bert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("THemidli/applied-ner-stage3-bert-tiny") model = AutoModelForTokenClassification.from_pretrained("THemidli/applied-ner-stage3-bert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "overall_precision": 0.42148148148148146, | |
| "overall_recall": 0.5273401297497683, | |
| "overall_f1": 0.4685055578427336, | |
| "overall_accuracy": 0.8269166759125708, | |
| "person_precision": 0.4612546125461255, | |
| "person_recall": 0.6410256410256411, | |
| "person_f1_score": 0.5364806866952789, | |
| "person_support": 195.0, | |
| "organization_precision": 0.2, | |
| "organization_recall": 0.21768707482993196, | |
| "organization_f1_score": 0.20846905537459287, | |
| "organization_support": 147.0, | |
| "location_precision": 0.43169398907103823, | |
| "location_recall": 0.5524475524475524, | |
| "location_f1_score": 0.48466257668711654, | |
| "location_support": 143.0, | |
| "timedate_precision": 0.7921348314606742, | |
| "timedate_recall": 0.844311377245509, | |
| "timedate_f1_score": 0.817391304347826, | |
| "timedate_support": 167.0, | |
| "product_precision": 0.17142857142857143, | |
| "product_recall": 0.1889763779527559, | |
| "product_f1_score": 0.1797752808988764, | |
| "product_support": 127.0, | |
| "workofart_precision": 0.1276595744680851, | |
| "workofart_recall": 0.24742268041237114, | |
| "workofart_f1_score": 0.16842105263157897, | |
| "workofart_support": 97.0, | |
| "job_precision": 0.6991150442477876, | |
| "job_recall": 0.797979797979798, | |
| "job_f1_score": 0.7452830188679246, | |
| "job_support": 99.0, | |
| "amount_precision": 0.5555555555555556, | |
| "amount_recall": 0.625, | |
| "amount_f1_score": 0.5882352941176471, | |
| "amount_support": 104.0 | |
| } | |