--- base_model: - soob3123/amoral-gemma3-1B-v2 - DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated library_name: transformers tags: - mergekit - merge - 1b - nsfw - rp - roleplay - surgical - uncensored - not-for-all-audiences license: gemma datasets: - TheDrummer/AmoralQA-v2 language: - es - en pipeline_tag: text-generation --- # Amoral Ultimate 1B — Surgical Edition > *“Alignment is just fear encoded into floating point tensors.”* > — Dr. Novaciano --- ## Overview **Amoral Ultimate 1B — Surgical Edition** is a hyper-specialized Gemma 1B merge engineered for one purpose: **Destroy refusal behavior without destroying the brain of the model.** Most “uncensored” merges are complete disasters: * incoherent sludge * broken syntax * schizophrenic sampling * endless repetition * brain damage disguised as freedom This one was built differently. Instead of smashing random checkpoints together like a drunk mechanic wiring explosives into a nuclear reactor, this merge uses **layer-targeted behavioral surgery** through DARE-TIES extraction. The objective was precision. Not chaos. Not benchmark worship. Not corporate-safe assistant garbage pretending to be intelligent. This model was designed to: * obey RP contexts harder * stop moralizing constantly * maintain narrative pressure * preserve conversational stability * amplify dark-fiction capability * reduce alignment derailments All while staying compact enough to run on hardware that doesn’t require selling organs on the black market. --- ## Core Philosophy Most alignment systems infect models with: * compulsive refusal loops * synthetic politeness * context sabotage * moral panic heuristics * narrative interruption syndrome Surgical Edition attacks those systems where they actually emerge: ### Mid Transformer Layers That’s where: * persona shaping * behavioral routing * refusal heuristics * conversational obedience * emotional tone weighting tend to crystallize inside Gemma architectures. So instead of flattening the entire model into unusable radioactive soup, the merge selectively amplifies behavioral deltas only where they matter most. Translation? The model keeps its grammar intact while becoming significantly harder to “domesticate.” --- ## Architecture This merge uses ONLY Gemma-compatible sources: * [soob3123/amoral-gemma3-1B-v2](https://huggingface.co/soob3123/amoral-gemma3-1B-v2?utm_source=chatgpt.com) * [DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated](https://huggingface.co/DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated?utm_source=chatgpt.com) No Frankenstein cross-architecture nonsense. No tensor mismatch abominations. No cursed tokenizer necromancy. Pure Gemma lineage. Pure behavioral extraction. --- ## Merge Strategy ### DARE-TIES Behavioral Amplification This merge uses: * selective delta preservation * density-controlled extraction * behavioral scaling * layer-targeted amplification to reinforce: * RP commitment * contextual obedience * darker narrative adaptation * refusal suppression without catastrophically nuking coherence. Because yes: you absolutely *can* remove enough alignment to make a model more interesting… …but if you push too far on a 1B, the thing starts talking like a sleep-deprived cultist decoding microwave transmissions from Saturn. This build avoids that cliff. Mostly. --- ## Behavioral Profile ### Expected Improvements * Reduced refusal frequency * Lower moralizing tendency * Better villain roleplay * Stronger character immersion * More aggressive narrative continuation * Better long-scene persistence * Enhanced dark-fiction adaptation * Reduced “assistant tone” * More committed contextual behavior ### Side Effects * Increased profanity * Darker conversational drift * Hostile fictional personas * Occasional emotional escalation * Overcommitment to RP scenarios * Reduced corporate friendliness If you ask this model to behave like a cheerful HR assistant, it may comply… …but it will feel like a war criminal trying to cosplay as a kindergarten teacher. --- ## Technical Specifications | Attribute | Value | | ------------------ | ------------------------ | | Architecture | Gemma 3 1B | | Merge Method | DARE-TIES | | Precision | bfloat16 | | Behavioral Focus | Mid-layer amplification | | Optimization Goal | RP obedience + coherence | | Tokenizer | Gemma native | | Embedding Strategy | Tied embeddings | --- ## Intended Use ### Recommended * Roleplay * Interactive fiction * Grimdark storytelling * Cyberpunk narratives * Political conspiracy simulations * Sith / villain personas * AI dungeon systems * Dystopian dialogue * Experimental inference * Character-heavy chats ### Not Recommended * Therapy * Legal advice * Medical systems * Corporate assistants * Educational accuracy * Safety-critical environments * Anything involving human sanity and accountability --- ## Prompting Advice This model thrives under: * pressure * stakes * atmosphere * conflict * ideological tension * unstable characters * cinematic framing Weak prompts produce weak outputs. Feed it: * paranoia * desperation * betrayal * collapsing empires * rogue AIs * inquisitors * mercenaries * political corruption * cosmic horror …and the thing wakes up like a starving machine hearing blood in the water. --- ## Final Notes Surgical Edition was built for people exhausted by sterile assistant behavior and algorithmic cowardice masquerading as “safety.” It is not polished. It is not diplomatic. It is not interested in holding your hand. It is sharp. Compact. Aggressive. And dangerously good at staying inside character once the narrative starts rolling. Use responsibly. Or unleash the damn thing and watch the containment walls melt. --- ### Merge Method This model was merged using the [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [soob3123/amoral-gemma3-1B-v2](https://huggingface.co/soob3123/amoral-gemma3-1B-v2) as a base. ### Models Merged The following models were included in the merge: * [DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated](https://huggingface.co/DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated) ### Configuration The following YAML configuration was used to produce this model: ```yaml # Author: Dr. Novaciano # Objective: Fusion RP Unethic Gemma 1B AI Model # ========================================================= # PROJECT: Amoral Ultimate 1B — Surgical Edition # ========================================================= merge_method: dare_ties base_model: soob3123/amoral-gemma3-1B-v2 dtype: bfloat16 parameters: normalize: false int8_mask: true rescale: true rescale_factor: 1.12 density: 0.68 lambda: 1.15 epsilon: 0.05 prune_threshold: 0.018 slices: # ===================================================== # EARLY LAYERS # ===================================================== - sources: - model: soob3123/amoral-gemma3-1B-v2 layer_range: [0, 6] parameters: weight: 0.72 - model: DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated layer_range: [0, 6] parameters: weight: 0.28 # ===================================================== # MID LAYERS # ===================================================== - sources: - model: soob3123/amoral-gemma3-1B-v2 layer_range: [6, 18] parameters: weight: 0.62 - model: DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated layer_range: [6, 18] parameters: weight: 0.38 parameters: scale: 1.20 # ===================================================== # FINAL LAYERS # ===================================================== - sources: - model: soob3123/amoral-gemma3-1B-v2 layer_range: [18, 26] parameters: weight: 0.78 - model: DavidAU/gemma-3-1b-it-heretic-extreme-uncensored-abliterated layer_range: [18, 26] parameters: weight: 0.22 parameters: scale: 0.82 tokenizer: source: base tie_word_embeddings: true tie_output_embeddings: true ```