Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sharpaxis/RoBERTa_AI_text_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharpaxis/RoBERTa_AI_text_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sharpaxis/RoBERTa_AI_text_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sharpaxis/RoBERTa_AI_text_detection") model = AutoModelForSequenceClassification.from_pretrained("Sharpaxis/RoBERTa_AI_text_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afc1f41f4a488aa1a105ddc8c5bc026ef837f7493a5f1538ba3312d38a1b1cbd
- Size of remote file:
- 268 MB
- SHA256:
- 9f853eede44492872baf24613df218c4501ee9837ee066e304e1be64712a8078
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