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
Commit History
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Support transformers 5 and refresh model card
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>de9a5e6
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support GPU inference
Verified signaturedd69ef6
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remove unecessary `peft` dependency
8f6b0b5
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update for pipeline
6f7b340
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updated files for hhem-2.1-open
e2b6d9e