Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
roberta
exbert
text-embeddings-inference
Instructions to use openai-community/roberta-base-openai-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai-community/roberta-base-openai-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openai-community/roberta-base-openai-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("openai-community/roberta-base-openai-detector") model = AutoModelForSequenceClassification.from_pretrained("openai-community/roberta-base-openai-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
Add model card
#2
by Marissa - opened
Looks good to me except that I think this sentence:
CONTENT WARNING: Readers should be aware this section may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.
Is too harsh IMO for a "detector model". Writing this without providing an example doesn't help here in my opinion and it's not something that should be added to every model card as a default as it scares users away
Merging to move forward, @patrickvonplaten you can address your comment in your follow-up PR if you feel strongly about it :-)
sgugger changed pull request status to merged