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t5-address-standardizer
DlBacyII/t5-address-standardizer
t5-address-standardizer is a machine learning model from DlBacyII. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model is t5-base fine-tuned to transform incorrect and non-standard addresses into standardized addresses.
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1.8 GB on disk
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At a glance
- Model type
- t5
- Access
- Public
- Created
- Oct 23, 2024
- Updated
- Oct 23, 2024
- SHA
- 58b832a6
Try a prompt
Model card
From the Hugging Face model README
Address Standardization and Correction Model
This model is t5-base fine-tuned to transform incorrect and non-standard addresses into standardized addresses.
How to use the model
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("Hnabil/t5-address-standardizer")
tokenizer = AutoTokenizer.from_pretrained("Hnabil/t5-address-standardizer")
inputs = tokenizer(
"220, soyth rhodeisland aveune, mason city, iowa, 50401, us",
return_tensors="pt"
)
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
# ['220, s rhode island ave, mason city, ia, 50401, us']
Training data
The model has been trained on data from openaddresses.io.
- Type
- t5
- Created
- Oct 23, 2024
- Updated
- Oct 23, 2024