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:
- fb193ac217cbdd29b52e1010c10f70ec0ae05fc877d1fb3a9782417a048cac32
- Size of remote file:
- 1.2 GB
- SHA256:
- 6857370c4d61159524cda82530a3a51a13ac3d591d20d5450b3fabf15f6847ab
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