Token Classification
Transformers
Safetensors
PyTorch
bert
ner
turkish
tr
dbmdz
bert-base-cased
bert-base-turkish-cased
Instructions to use nextgeo/address-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nextgeo/address-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nextgeo/address-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nextgeo/address-extraction") model = AutoModelForTokenClassification.from_pretrained("nextgeo/address-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nextgeo/address-extraction: direct link, hf CLI and curl.
- Browser
- Download file 755 kB
-
https://huggingface.co/nextgeo/address-extraction/resolve/main/tokenizer.json
- Command line
-
hf download hf://nextgeo/address-extraction/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nextgeo/address-extraction/resolve/main/tokenizer.json
755 kB
File too large to display, you can check the raw version instead.