Model Details
Full Model IDopenai-community/roberta-base-openai-detector
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)893.9K
Likes132
Last Modified2/19/2024
Author / Orgopenai-community
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-classification", model="openai-community/roberta-base-openai-detector")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfjaxsafetensorsrobertatext-classificationexbertendataset:bookcorpusdataset:wikipediaarxiv:1904.09751arxiv:1910.09700arxiv:1908.09203license:mittext-embeddings-inferenceendpoints_compatibledeploy:azureregion:us
More Text Classification Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🏷️ Task: Text Classification
This model is designed for the Text Classification task. Explore more models for this use case.
All Text Classification Models →📊 Popularity
⬇ Downloads893.9K
❤️ Community Likes132
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.