LettuceDetect: Hallucination Detection Model Model Name: lettucedect large modernbert en v1 Organization: KRLabsOrg Github: https://github.com/KRLabsOrg/LettuceDetect Overview LettuceDetect is a transformer based model for hallucination detection on context and answer pairs, designed for Retrieval Augmented Generation (RAG) applications. This model is built on ModernBERT , which has been specifically chosen and trained becasue of its extended context support (up to 8192 tokens ). This long context capability is critical for tasks where detailed and extensive documents need to be processed to accurately determine if an answer is supported by the provided context. This is our Large model based on ModernBERT large Model Details Architecture: ModernBERT (Large) with extended context support (up to 8192 tokens) Task: Token Classification / Hallucination Detection Training Dataset: RagTruth Language: English How It Works The model is trained to identify tokens in the answer text that are not supported by the given context. During inference, the model returns token level predictions which are then aggregated into spans. This allows users to see exactly which parts of the answer are consid…
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