Instructions to use privacy-tech-lab/ZipBaseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use privacy-tech-lab/ZipBaseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="privacy-tech-lab/ZipBaseModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("privacy-tech-lab/ZipBaseModel") model = AutoModelForSequenceClassification.from_pretrained("privacy-tech-lab/ZipBaseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
widget:
- text: >-
'.54.133.36\\"}, \\"geo_country\\":\\"US\\",
\\"geo_countryname\\":\\"United States\\",
\\"geo_subdivision\\":\\"Arizona\\", \\"geo_zip\\":\\"<TARGET_ZIP>\\",
\\"geo_city\\":\\"Phoenix\\", \\"geo_lat\\":\\"33.4361\\",
\\"geo_long\\":\\"-112.024\\",
\\"requestMuid\\":\\"notFound\\"}}}","usphx_149"'
example_title: Zip True Positive Example
- text: >-
'-2 {\\\\n height: 93px;\\\\n width:
100%;\\\\n}\\\\n#banner-native-oferta-<TARGET_ZIP>-2 > div {\\\\n
float: left;\\\\n width:
100%!important;\\\\n}\\\\n#banner-native-oferta-00100-2 > div > iframe
{\\\\n width: 100%!important;\\\\n height:
95px!important;\\\\n}\\\\'
example_title: Zip False Positive Example