Model Card This model is designed to categorize text into two classes: "safe", or "nsfw" (not safe for work), which makes it suitable for content moderation and filtering applications. The model was trained using a dataset containing 190,000 labeled text samples, distributed among the two classes of "safe" and "nsfw". The model is based on the Distilbert base model. In terms of performance, the model has achieved a score of 0.974 for F1 (40K exemples). To improve the performance of the model, it is necessary to preprocess the input text. You can refer to the preprocess function in the app.py file in the following space: . Model Description The model can be used directly to classify text into one of the two classes. It takes in a string of text as input and outputs a probability distribution over the two classes. The class with the highest probability is selected as the predicted class. Developed by: Elias Al Bouzidi, Massine El Khader, Abdellah Oumida, Mohammed Sbaihi, Eliott Binard Model type: 60M Language (NLP): English License: apache 2.0 Technical Paper: A more detailed technical overview of the model and the dataset can be found here. Uses The model can be integrated into larg…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy