Text Classification
Transformers
Safetensors
roberta
safety
judge
probguard
calibeval
text-embeddings-inference
Instructions to use hxz-sec/CalibEval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hxz-sec/CalibEval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hxz-sec/CalibEval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hxz-sec/CalibEval") model = AutoModelForSequenceClassification.from_pretrained("hxz-sec/CalibEval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2456ab9a1b7c2697ae4df6cd162acb77aecbfc578dc15077fe545215cb4539d8
- Size of remote file:
- 5.27 kB
- SHA256:
- 0a1df8fc443e4852e0cc357ed89ccfbf0244f95e3bb97863a271cdd5f837e822
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