Text Classification
Transformers
English
multi-label-classification
dialogue
conversational-ai
gricean-maxims
cooperative-communication
deberta
nlp
pragmatics
Eval Results (legacy)
Instructions to use Pushkar27/GriceBench-Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pushkar27/GriceBench-Detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pushkar27/GriceBench-Detector")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pushkar27/GriceBench-Detector", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload temperatures.json with huggingface_hub
Browse files- temperatures.json +6 -0
temperatures.json
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{
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"quantity": 0.1,
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"quality": 0.5818822841463992,
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"relation": 0.1,
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"manner": 0.6515716212629745
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