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Austin-Groundsetter
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deberta-prism-v2

Text Classification
Transformers
Safetensors
deberta-v2
multi-label-classification
compliance
prism
text-embeddings-inference
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="Austin-Groundsetter/deberta-prism-v2")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Austin-Groundsetter/deberta-prism-v2")
model = AutoModelForSequenceClassification.from_pretrained("Austin-Groundsetter/deberta-prism-v2")
Quick Links

DeBERTa PRISM v2

Multi-label compliance violation classifier for peptide, hemp, and supplement websites.

  • Base model: microsoft/deberta-v3-large
  • Labels: 25 (22 violation + 3 compliant)
  • Macro F1: 0.997
  • Architecture: DebertaV2ForSequenceClassification
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Tensor type
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