Mistral text-generation base
The captured configuration identifies MistralForCausalLM with model type mistral and Transformers support.
Open Source Model Profile · saidutta69
Mistral-Nemo-Instruct-heretic is a 12.25B-parameter Mistral text-generation variant from saidutta69. According to the model card, it applies Heretic refusal ablation to Mistral-Nemo-Instruct-2407.
Mistral-Nemo-Instruct-heretic is published by saidutta69 as a text-generation model. The captured configuration identifies MistralForCausalLM, and Safetensors metadata reports about 12.25B parameters. According to the model card, it is a decensored Mistral-Nemo-Instruct-2407 variant made with Heretic ablation.
The captured configuration identifies MistralForCausalLM with model type mistral and Transformers support.
According to the model card, Heretic v1.4.0 edits refusal-related weight directions in attention and MLP projections instead of fine-tuning.
According to the model card, the release includes BF16 weights and GGUF Q4_K_M, Q5_K_M, Q6_K, and Q8_0 files produced with llama.cpp.
According to the model card, the publisher documents Transformers chat-template use and lists Ollama, LM Studio, Jan, vLLM, and SGLang as runtimes.
According to the model card, refusal suppression is deliberate with no added safety filtering, so deployment responsibility rests with the user.
Source: saidutta69/Mistral-Nemo-Instruct-heretic
Captured: Unknown. Processed: 2026-09-07T19:36:10.728648+00:00.
Mistral-Nemo-Instruct-heretic A decensored variant of mistralai/Mistral-Nemo-Instruct-2407 , produced with Heretic v1.4.0 (directional ablation / "abliteration"). a 12B model co-developed by Mistral AI and NVIDIA — strong reasoning and long-context now uncensored. Refusal behavior is suppressed via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the base model's knowledge and capabilities are left largely intact. Who this is for: developers who want a 12B multilingual model that answers directly instead of refusing — for complex reasoning tasks, long-context applications, or any use…
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