Text Classification
Transformers
TensorBoard
ONNX
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use trentmkelly/slop-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trentmkelly/slop-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trentmkelly/slop-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trentmkelly/slop-detector") model = AutoModelForSequenceClassification.from_pretrained("trentmkelly/slop-detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b4673c8b0403100bc41828673574041ae53fe180f3c80ee2cf22c0c58934945
- Size of remote file:
- 5.37 kB
- SHA256:
- 7cb80b880983dad90e2001410afc3b3aad5340c8f3467534951dc6ceb9eca388
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