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:
- b56bafc60cacd897ebff62ac654b671aaaece8948897cdcc0995188ee81d2411
- Size of remote file:
- 1.11 GB
- SHA256:
- 360114df2a5b26cdf66016c59c55f186c67f6d6f74d21493de05df6681558b4a
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