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)# 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
update HHEM-2.1-Open demo link
Browse files
README.md
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<img src="https://huggingface.co/vectara/hallucination_evaluation_model/resolve/main/candle.png" width="50" height="50" style="display: inline;"> In Loving memory of Simon Mark Hughes...
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<iframe src="https://vectara-hhem-2-1-open-demo.hf.space/" title="Demo for HHEM-2.1-Open"></iframe>
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<img src="https://huggingface.co/vectara/hallucination_evaluation_model/resolve/main/candle.png" width="50" height="50" style="display: inline;"> In Loving memory of Simon Mark Hughes...
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Click [here](https://huggingface.co/spaces/vectara/hhem-2.1-open-demo) for HHEM-2.1-Open demo app.
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<iframe src="https://vectara-hhem-2-1-open-demo.hf.space/" title="Demo for HHEM-2.1-Open"></iframe>
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