Text Classification
Transformers
PyTorch
English
distilbert
distilroberta
sentiment
NSFW
inappropriate
spam
twitter
reddit
text-embeddings-inference
Instructions to use michelleli99/NSFW_text_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michelleli99/NSFW_text_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michelleli99/NSFW_text_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michelleli99/NSFW_text_classifier") model = AutoModelForSequenceClassification.from_pretrained("michelleli99/NSFW_text_classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
Fine-tuned DistilRoBERTa-base for NSFW Classification
Model Description
DistilBERT is a transformer model that performs sentiment analysis. I fine-tuned the model on Reddit posts with the purpose of classifying not safe for work (NSFW) content, specifically text that is considered inappropriate and unprofessional. The model predicts 2 classes, which are NSFW or safe for work (SFW).
The model is a fine-tuned version of DistilBERT.
It was fine-tuned on 14317 Reddit posts pulled from the (Reddit API) [https://praw.readthedocs.io/en/stable/].
How to Use
from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="michellejieli/NSFW_text_classification")
classifier("I see you’ve set aside this special time to humiliate yourself in public.")
Output:
[{'label': 'NSFW', 'score': 0.998853325843811}]
Contact
Please reach out to michelle.li851@duke.edu if you have any questions or feedback.
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