Instructions to use THemidli/applied-ner-stage4-bert-tiny-improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use THemidli/applied-ner-stage4-bert-tiny-improved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="THemidli/applied-ner-stage4-bert-tiny-improved")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("THemidli/applied-ner-stage4-bert-tiny-improved") model = AutoModelForTokenClassification.from_pretrained("THemidli/applied-ner-stage4-bert-tiny-improved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "overall_precision": 0.42610652663165793, | |
| "overall_recall": 0.5264133456904542, | |
| "overall_f1": 0.4709784411276949, | |
| "overall_accuracy": 0.8332408742926883, | |
| "person_precision": 0.48659003831417624, | |
| "person_recall": 0.6512820512820513, | |
| "person_f1_score": 0.5570175438596492, | |
| "person_support": 195.0, | |
| "organization_precision": 0.21637426900584794, | |
| "organization_recall": 0.25170068027210885, | |
| "organization_f1_score": 0.23270440251572325, | |
| "organization_support": 147.0, | |
| "location_precision": 0.43575418994413406, | |
| "location_recall": 0.5454545454545454, | |
| "location_f1_score": 0.48447204968944096, | |
| "location_support": 143.0, | |
| "timedate_precision": 0.7853107344632768, | |
| "timedate_recall": 0.8323353293413174, | |
| "timedate_f1_score": 0.8081395348837209, | |
| "timedate_support": 167.0, | |
| "product_precision": 0.1678832116788321, | |
| "product_recall": 0.18110236220472442, | |
| "product_f1_score": 0.17424242424242423, | |
| "product_support": 127.0, | |
| "workofart_precision": 0.13636363636363635, | |
| "workofart_recall": 0.24742268041237114, | |
| "workofart_f1_score": 0.1758241758241758, | |
| "workofart_support": 97.0, | |
| "job_precision": 0.6638655462184874, | |
| "job_recall": 0.797979797979798, | |
| "job_f1_score": 0.724770642201835, | |
| "job_support": 99.0, | |
| "amount_precision": 0.5398230088495575, | |
| "amount_recall": 0.5865384615384616, | |
| "amount_f1_score": 0.5622119815668203, | |
| "amount_support": 104.0 | |
| } | |