Text Classification
Transformers
Safetensors
English
Chinese
deberta-v2
manipulative-language
social-psychology
text-embeddings-inference
Instructions to use LilithHu/mbert-manipulative-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LilithHu/mbert-manipulative-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LilithHu/mbert-manipulative-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LilithHu/mbert-manipulative-detector") model = AutoModelForSequenceClassification.from_pretrained("LilithHu/mbert-manipulative-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| training_args.bin filter=lfs diff=lfs merge=lfs -text | |
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |
| spm.model filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |