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
Delete rng_state.pth
Browse files- rng_state.pth +0 -3
rng_state.pth
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