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
| { | |
| "epoch": 15.0, | |
| "eval_0_to_0": 9464, | |
| "eval_0_to_1": 575, | |
| "eval_1_to_0": 708, | |
| "eval_1_to_1": 9253, | |
| "eval_accuracy": 0.93585, | |
| "eval_loss": 0.5719918608665466, | |
| "eval_runtime": 107.5664, | |
| "eval_samples": 20000, | |
| "eval_samples_per_second": 185.932, | |
| "eval_steps_per_second": 11.621 | |
| } |