Text Classification
Transformers
Safetensors
English
HHEMv2Config
hallucination-detection
factual-consistency
rag
custom_code
Instructions to use vectara/hallucination_evaluation_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vectara/hallucination_evaluation_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vectara/hallucination_evaluation_model", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("vectara/hallucination_evaluation_model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download candle.png from vectara/hallucination_evaluation_model: direct link, hf CLI and curl.
- Browser
- Download file 487 kB
-
https://huggingface.co/vectara/hallucination_evaluation_model/resolve/main/candle.png
- Command line
-
hf download hf://vectara/hallucination_evaluation_model/candle.png
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curl -L -o candle.png https://huggingface.co/vectara/hallucination_evaluation_model/resolve/main/candle.png
487 kB
