Instructions to use privacy-tech-lab/CityBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/CityBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/CityBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/CityBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/CityBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
widget:
- text: >-
'"Europe","continent_code":"EU","country":"Portugal","country_code":"PT","state":"","city":"","postal":"","time_zone":"Europe/<TARGET_CITY>","region":"EMEA","ipAddress":"94.46.24.35","latitude":38.7057,"longitude":-9.1359}'
example_title: City True Positive Example
- text: >-
'ass="cover-image__popup-view__caption-wrapper text-white"><p><b>ONLINE
COVER</b> Boosting Immunity. The image shows a man in <TARGET_CITY>
receiving a second dose of the Pfizer-BioNTech COVID-19 vaccine in late
January 2021 during the launch of Israel’s SARS-CoV-'
example_title: City False Positive Example