Instructions to use mathislucka/deberta-hallucination-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mathislucka/deberta-hallucination-eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mathislucka/deberta-hallucination-eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mathislucka/deberta-hallucination-eval") model = AutoModelForSequenceClassification.from_pretrained("mathislucka/deberta-hallucination-eval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 594ac0b9850c1e2b424780a3659c5fa13e8594bb8ce494748440ccadaa7e8f04
- Size of remote file:
- 1.48 GB
- SHA256:
- 97f31eceff5a1264f3a1ae519cb45e624fa9b337d255f869f44f5b6120b433c7
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