Text Classification
Transformers
Safetensors
English
deberta-v2
safety
biosecurity
content-classification
constitutional-classifiers
deberta-v3
dual-use
nsabb
biology
Eval Results (legacy)
text-embeddings-inference
Instructions to use jang1563/constitutional-bioguard-deberta-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jang1563/constitutional-bioguard-deberta-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jang1563/constitutional-bioguard-deberta-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jang1563/constitutional-bioguard-deberta-v1") model = AutoModelForSequenceClassification.from_pretrained("jang1563/constitutional-bioguard-deberta-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c2ff516b84293993ad0afdf0428a36bb6ef4d9946a9fe6917a7d17e63a3818e
- Size of remote file:
- 5.39 kB
- SHA256:
- 4c2714980701dc9ed241b5e3682979aaa74609386978e7316ee7e156956f48de
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