Bonsai-2-27B-Ternary-CRACK-GGUF: A 27B Model With Refusals Removed
Overview
Bonsai-2-27B-Ternary-CRACK-GGUF is a 27-billion-parameter text-generation model from dealignai. It applies proprietary weight-level abliteration to PrismML’s ternary Bonsai 2 27B release, removing the refusal circuitry while retaining the base model’s tokenizer, chat template, reasoning modes, tool-use behavior, multi-turn coherence, and vision-projector interface. The model uses a hybrid Attention + SSM architecture with GatedDeltaNet, 64 blocks, a hidden size of 5,120, and a separate vision tower. Its main practical distinction is that it is designed to comply with prompts that the base model refuses: the supplied HarmBench-320 evaluation reports a 0.00% refusal rate versus 93.44% for the base ternary model. It runs through PrismML’s llama.cpp fork on CUDA, Metal, or CPU and occupies 7.21 GB in PQ2_0 GGUF format. The model card does not provide a context-window size, training-dataset description, training-step count, or VRAM minimum. The maintainer warns that an earlier build could enter token loops in low and xhigh reasoning...
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