Text Classification
Transformers
ONNX
Safetensors
roberta
llm-guard
security
text-embeddings-inference
Instructions to use TangoBeeAkto/distilroberta-rejection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TangoBeeAkto/distilroberta-rejection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TangoBeeAkto/distilroberta-rejection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TangoBeeAkto/distilroberta-rejection") model = AutoModelForSequenceClassification.from_pretrained("TangoBeeAkto/distilroberta-rejection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c142666d5f87fcf1f62418ddd41ebd46e5a605ed0ea49bb9a0b78f81a8392c31
- Size of remote file:
- 4.66 kB
- SHA256:
- ef62f442414f3b3b31779f3d95e055f5ddf5734a391074a87ea42323ce67c246
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