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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PragmaticMachineLearning/address-norm") model = AutoModelForSeq2SeqLM.from_pretrained("PragmaticMachineLearning/address-norm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from PragmaticMachineLearning/address-norm: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/PragmaticMachineLearning/address-norm/resolve/main/model.safetensors
- Command line
-
hf download hf://PragmaticMachineLearning/address-norm/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/PragmaticMachineLearning/address-norm/resolve/main/model.safetensors
1.2 GB
- Xet hash:
- 893356da7504c5bd94b2ccccaded4324ce5e398f21205dcb05f7755b38d3fe4c
- Size of remote file:
- 1.2 GB
- SHA256:
- 6fdc56296bf87a33234b189d4d77f30c4f8df8564f4ff4919fc74fb312050f5c
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