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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ffea8b27bc426fb91fd2546016776baa6f157b707a39a2678d60ba1bce18237
- Size of remote file:
- 5.24 kB
- SHA256:
- 9ce6baaaff44c352d24cc6854b2501d7953617fc2eba8a1aae469929cd136bf4
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