Instructions to use ctrlbuzz/bert-addresses with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctrlbuzz/bert-addresses with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ctrlbuzz/bert-addresses")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ctrlbuzz/bert-addresses") model = AutoModelForTokenClassification.from_pretrained("ctrlbuzz/bert-addresses", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ctrlbuzz/bert-addresses: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/ctrlbuzz/bert-addresses/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ctrlbuzz/bert-addresses/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ctrlbuzz/bert-addresses/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 77effdcffbca24bfe6fadc57c0811ecff88b3e3dfa7b500da6331028d45d415f
- Size of remote file:
- 431 MB
- SHA256:
- e7a8ddeccd6c42019298ba733a80c6203f741f217472cd47310838568e6eb175
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