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:
- cce35dd3ebbf19a4f20ce4b1ef8974b98d9dd76362407e6f85dbcf91eeea6e09
- Size of remote file:
- 1.47 kB
- SHA256:
- c1d14f5469c2a4038fad184a1550b1158725c35f1abb35eebc16618718fd59da
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