Text Classification
Transformers
Safetensors
deberta-v2
multi-label-classification
compliance
prism
text-embeddings-inference
Instructions to use Austin-Groundsetter/deberta-prism-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Austin-Groundsetter/deberta-prism-v2 with Transformers:
# 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
0f3973a | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:25107a6741ba46ecd2e6943e94dcbeac730cff054ecd5c2e3620278a64f4ffce
size 4920
|