This collection includes our hungarian models using the recently released multilingual ModernBERT models
AI & ML interests
Explainable AI, Rule-based models, Rule learning with LLMs, Hallucination detection, Fact checking LLMs
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These are our EuroBERT fine-tunes on our translated RAGTruth datasets.
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KRLabsOrg/lettucedect-610m-eurobert-de-v1
Token Classification • 0.6B • Updated • 24 • 1 -
KRLabsOrg/lettucedect-210m-eurobert-de-v1
Token Classification • 0.2B • Updated • 2 -
KRLabsOrg/lettucedect-610m-eurobert-fr-v1
Token Classification • 0.6B • Updated • 2 • 1 -
KRLabsOrg/lettucedect-610m-eurobert-cn-v1
Token Classification • 0.6B • Updated • 18 • 1
This collection includes our translated training data that we've used to create multilingual hallucination detection models.
This Collection contains our small, Ettin-encoder (https://arxiv.org/abs/2507.11412) based models trained on synthetic and RagTruth data.
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KRLabsOrg/tinylettuce-ettin-17m-en-bioasq
Token Classification • 16.9M • Updated • 64 • 7 -
KRLabsOrg/tinylettuce-ettin-68m-en-bioasq
Token Classification • 68.4M • Updated • 3 • 2 -
KRLabsOrg/tinylettuce-ettin-32m-en-bioasq
Token Classification • 32M • Updated • 1 • 1 -
KRLabsOrg/tinylettuce-ettin-68m-en
Token Classification • 68.4M • Updated • 641 • 2
Trained ModernBERT (base and large) for detection hallucinations in LLM responses. The models are trained as token classifications.
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KRLabsOrg/lettucedect-base-modernbert-en-v1
Token Classification • 0.1B • Updated • 885 • 17 -
KRLabsOrg/lettucedect-large-modernbert-en-v1
Token Classification • 0.4B • Updated • 203 • 28 -
LettuceDetect: A Hallucination Detection Framework for RAG Applications
Paper • 2502.17125 • Published • 12 -
7
LettuceDetect
🥬Let Us Detect your hallucinations! Demo for our framework.
This collection includes our hungarian models using the recently released multilingual ModernBERT models
This Collection contains our small, Ettin-encoder (https://arxiv.org/abs/2507.11412) based models trained on synthetic and RagTruth data.
-
KRLabsOrg/tinylettuce-ettin-17m-en-bioasq
Token Classification • 16.9M • Updated • 64 • 7 -
KRLabsOrg/tinylettuce-ettin-68m-en-bioasq
Token Classification • 68.4M • Updated • 3 • 2 -
KRLabsOrg/tinylettuce-ettin-32m-en-bioasq
Token Classification • 32M • Updated • 1 • 1 -
KRLabsOrg/tinylettuce-ettin-68m-en
Token Classification • 68.4M • Updated • 641 • 2
These are our EuroBERT fine-tunes on our translated RAGTruth datasets.
-
KRLabsOrg/lettucedect-610m-eurobert-de-v1
Token Classification • 0.6B • Updated • 24 • 1 -
KRLabsOrg/lettucedect-210m-eurobert-de-v1
Token Classification • 0.2B • Updated • 2 -
KRLabsOrg/lettucedect-610m-eurobert-fr-v1
Token Classification • 0.6B • Updated • 2 • 1 -
KRLabsOrg/lettucedect-610m-eurobert-cn-v1
Token Classification • 0.6B • Updated • 18 • 1
Trained ModernBERT (base and large) for detection hallucinations in LLM responses. The models are trained as token classifications.
-
KRLabsOrg/lettucedect-base-modernbert-en-v1
Token Classification • 0.1B • Updated • 885 • 17 -
KRLabsOrg/lettucedect-large-modernbert-en-v1
Token Classification • 0.4B • Updated • 203 • 28 -
LettuceDetect: A Hallucination Detection Framework for RAG Applications
Paper • 2502.17125 • Published • 12 -
7
LettuceDetect
🥬Let Us Detect your hallucinations! Demo for our framework.
This collection includes our translated training data that we've used to create multilingual hallucination detection models.