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:
- 715845cf36bd1d54e5517e4e8f146e2dc5bbafa07366353e81f35666e2aad116
- Size of remote file:
- 1.43 GB
- SHA256:
- 37d6f8068b030fc850fda9f4f39d69176db0609ccbdc0d45a52327bd5551afe7
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