Token Classification
Transformers
Safetensors
English
distilbert
document-understanding
procurement
india
gem
synthetic-data
Instructions to use HarshilDaGoat/gem-certificate-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HarshilDaGoat/gem-certificate-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HarshilDaGoat/gem-certificate-extractor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HarshilDaGoat/gem-certificate-extractor") model = AutoModelForTokenClassification.from_pretrained("HarshilDaGoat/gem-certificate-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download field_eval.json from HarshilDaGoat/gem-certificate-extractor: direct link, hf CLI and curl.
- Browser
- Download file 1.51 kB
-
https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/field_eval.json
- Command line
-
hf download hf://HarshilDaGoat/gem-certificate-extractor/field_eval.json
-
curl -L -o field_eval.json https://huggingface.co/HarshilDaGoat/gem-certificate-extractor/resolve/main/field_eval.json
1.51 kB
| { | |
| "model": { | |
| "overall_accuracy": 0.9999, | |
| "overall_false_positive_rate": 0.0, | |
| "per_field": { | |
| "gstin": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 1174 | |
| }, | |
| "pan": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 593 | |
| }, | |
| "udyam_number": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 902 | |
| }, | |
| "cin": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 124 | |
| }, | |
| "establishment_code": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 311 | |
| }, | |
| "dpiit_number": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 312 | |
| }, | |
| "trade_name": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 296 | |
| }, | |
| "legal_name": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": null, | |
| "support": 3000 | |
| }, | |
| "activity": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 902 | |
| }, | |
| "enterprise_category": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 901 | |
| }, | |
| "local_content_pct": { | |
| "accuracy": 0.9966, | |
| "false_positive_rate": 0.0, | |
| "support": 296 | |
| }, | |
| "valid_until": { | |
| "accuracy": 1.0, | |
| "false_positive_rate": 0.0, | |
| "support": 784 | |
| } | |
| } | |
| } | |
| } |