Instructions to use privacy-tech-lab/RegionModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/RegionModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/RegionModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/RegionModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/RegionModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
widget:
- text: >-
'{"ip_address":"45.8.223.197","country_name":"Japan","country_iso_code":"JP","state":"<TARGET_REGION>","state_iso_code":"27","city":"Osaka","city_id":1853909,"city_confidence":-1,"postal_code":"543-0062","latitude":34.6946,"lo'
example_title: Region True Positive Example
- text: >-
' is an animal welfare issue as well as wasting time of vets and carers
who rescue and treat these injured animals for free.\\n<TARGET_REGION> has
banned these products as has Iceland, New Zealand and Ireland. Scotland
has said they will ban them. Our birds, Microbat'
example_title: Region False Positive Example