Token Classification
Transformers
PyTorch
English
Hindi
ner
address-parsing
indian-addresses
bert
crf
Eval Results (legacy)
Instructions to use howdoiuse-keyboard/indian-address-parser-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howdoiuse-keyboard/indian-address-parser-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="howdoiuse-keyboard/indian-address-parser-model")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("howdoiuse-keyboard/indian-address-parser-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_f1": 0.8758002560819462, | |
| "best_precision": 0.8571428571428571, | |
| "best_recall": 0.8952879581151832, | |
| "epoch": 14, | |
| "model_name": "ai4bharat/IndicBERTv2-SS", | |
| "use_crf": true, | |
| "learning_rate": 5e-05, | |
| "crf_learning_rate": 0.001, | |
| "lr_decay": 0.95, | |
| "warmup_ratio": 0.1, | |
| "train_samples": 3935, | |
| "val_samples": 64 | |
| } |