MiniMax M2.7 abliterated weights drop in BF16 and GGUF formats
llmfan46 released uncensored weights for MiniMax M2.7 this week, shipping both BF16 safetensors and quantized GGUF formats with safety layers removed.
MiniMax-M2.7-BF16-ultra-uncensored-heretic is an abliterated version of MiniMax's M2.7 text-generation model, released by llmfan46 on HuggingFace on May 14. The weights ship in full-precision BF16 safetensors format with safety tuning stripped out, tagged as "heretic," "uncensored," "decensored," and "abliterated." A companion GGUF quantized release followed hours later the same day, making the model accessible to users running llama.cpp or other GGUF-compatible inference engines on consumer hardware.
Abliteration has become a common technique in the open-weight community for stripping safety layers from foundation models without retraining — practitioners target specific attention heads or layer ranges believed to encode refusal responses, then zero them out or interpolate around them. The approach preserves most of the model's general capabilities while eliminating canned refusal replies. Both repos carry the same abliteration treatment; the model card does not detail the method. The GGUF release also carries an "ara" tag, which may indicate Arabic language support or a specific quantization profile.