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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("howdoiuse-keyboard/indian-address-parser-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.3c17467
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Add base_model, library_name, pipeline_tag to model card metadata
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Update README.md
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v4 model
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Update training_info.json
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Update test_results.json
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Add model card
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Upload IndicBERTv2-CRF model (80% F1 on Indian addresses)
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initial commit
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