Instructions to use PragmaticMachineLearning/address-norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PragmaticMachineLearning/address-norm with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PragmaticMachineLearning/address-norm") model = AutoModelForSeq2SeqLM.from_pretrained("PragmaticMachineLearning/address-norm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6212d653a656dd2fb77772bcb31c2b6d21486b68bca3d7adcfe8b83380e085a8
- Size of remote file:
- 3.58 kB
- SHA256:
- 02e84591dcd772db28df2f332752f507b230ad67972c760e3dd2b0d5f1b7ce5f
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