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Animised NLI Contradiction Detector v3

prajjwal1/bert-medium (41M) trained directly on hard labels
with a 3:1 imbalanced dataset to prevent contradiction bias.

Upgrade from bert-small to bert-medium for stronger performance,
while keeping the conservative contradiction policy from v2.

0 = entailment | 1 = neutral | 2 = contradiction

from transformers import pipeline
clf = pipeline("text-classification", model="Animised/nli-cdv3")
clf("Premise [SEP] Hypothesis", top_k=None)

Character fact consistency checker for the
Animised project.

Safetensors

Model size

41.4M params

Tensor type

F32

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