Text Classification
Transformers
TensorBoard
Safetensors
English
deberta
legal
multi-label-classification
terms-of-service
unfair-clauses
Instructions to use Agreemind/deberta-unfair-tos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Agreemind/deberta-unfair-tos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Agreemind/deberta-unfair-tos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Agreemind/deberta-unfair-tos") model = AutoModelForSequenceClassification.from_pretrained("Agreemind/deberta-unfair-tos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c181f0112175a1993f2ac52d4bbc51123ca8b68badaa2a57876f6ec8dfa5049f
- Size of remote file:
- 5.84 kB
- SHA256:
- 4875e7651cf5c03dc879140443be9ee0c8020d5611acd7c8e793d35847d95db8
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