Text Classification
Transformers
PyTorch
JAX
Safetensors
English
roberta
exbert
text-embeddings-inference
Instructions to use openai-community/roberta-large-openai-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai-community/roberta-large-openai-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openai-community/roberta-large-openai-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("openai-community/roberta-large-openai-detector") model = AutoModelForSequenceClassification.from_pretrained("openai-community/roberta-large-openai-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7548895bb2c6453ef991866e6d122389871477f74ab86cf57621df075af8cbe
- Size of remote file:
- 1.42 GB
- SHA256:
- eab982afbd041450e68dfa46fd74566725a74686cf483a6a573a5b7068c666bb
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