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
File size: 399 Bytes
e5a4711 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"is_local": true,
"mask_token": "<mask>",
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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