| --- | |
| datasets: | |
| - privacy_policy_dataset | |
| language: | |
| - en | |
| library_name: transformers | |
| license: mit | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| pipeline_tag: text-classification | |
| tags: | |
| - privacy | |
| - legal | |
| - compliance | |
| - NLP | |
| --- | |
| # Privacy Policy Model | |
| This model is trained to classify privacy policies into multiple categories, including Data Collection, Data Sharing, User Rights, etc. | |
| ## Model Details | |
| - **Model Type**: BERT-based Sequence Classification | |
| - **Languages**: English | |
| - **Library**: Transformers | |
| - **Pipeline Tag**: text-classification | |
| ## Usage | |
| To use this model, you can load it via the `transformers` library: | |
| ```python | |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
| model_name = "1kazmi/privacy-policy-model" | |
| model = AutoModelForSequenceClassification.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |