Instructions to use ARI-HIPA-AI-Team/HIPA-AI_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ARI-HIPA-AI-Team/HIPA-AI_Model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ARI-HIPA-AI-Team/HIPA-AI_Model") - Notebooks
- Google Colab
- Kaggle
HIPA-AI ML Model: Keras
This model takes paragraph style reddit posts and predicts whether they are a violation of the Health Insurance Portability and Accountability Act.
Source
This model was the first place finisher in the HIPA-AI Model competition hosted by Codalab with a score of 70% accuracy. It was authored by tarak2134.
Details
This model takes a text body between 40 and 750 words as input. As output, the model gives a binary; "yes, this is a violation", or "no, this is not a violation" The model tends to be more accurate on larger bodies of text.
Dataset
This model was trained on an annotated set of 100 reddit posts. To get more information, see the dataset card at ARI-HIPA-AI-Team/Dataset
Model Card Authors
Brayden Cloutier
Model Card Contact
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Dataset used to train ARI-HIPA-AI-Team/HIPA-AI_Model
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